Prompting a Pretrained Transformer Can Be a Universal Approximator
Aleksandar Petrov, Philip H.S. Torr, Adel Bibi

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When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
Aleksandar Petrov, Philip H.S. Torr, Adel Bibi
ICLR 2024
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Language Model Tokenizers Introduce Unfairness Between Languages
Aleksandar Petrov, Emanuele La Malfa, Philip H.S. Torr, Adel Bibi
NeurIPS 2023
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Certifying Ensembles: A General Certification Theory with S-Lipschitzness
Aleksandar Petrov*, Francisco Eiras, Amartya Sanyal, Philip H.S. Torr, Adel Bibi*
ICML 2023
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Real-Time Evaluation in Online Continual Learning: A New Hope
Yasir Ghunaim*, Adel Bibi*, Kumail Alhamoud, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Ameya Prabhu, Philip H. S. Torr, Bernard Ghanem
Oral in CVPR, 2023
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Sample-dependent Adaptive Temperature Scaling for Improved Calibration
Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania
AAAI, 2023
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RANCER: Non-Axis Aligned Anisotropic Certification With Randomized Smoothing
Taras Rumezhak, Francisco Girbal Eiras, Philip HS Torr, Adel Bibi
WACV, 2023
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Linear Complexity Self-Attention with 3rd Order Polynomials
Francesca Babiloni, Ioannis Marras, Jiankang Deng, Filippos Kokkinos, Matteo Maggioni,Grigorios Chrysos, Philip Torr and Stefanos Zafeiriou
2023 IEEE Conference of Computer Vision and Pattern Recognition
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Fairness in AI and Its Long-Term Implications on Society
Ondrej Bohdal, Timothy Hospedales, Philip H.S. Torr, Fazl Barez
3rd Annual Stanford Existential Risks Conference, 2023
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Deeply Explain CNN via Hierarchical Decomposition
Ming-Ming Cheng, Peng-Tao Jiang, Ling-Hao Han, Liang Wang, Philip Torr
AAAI, 2023
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Certifying Ensembles: A General Certification Theory with S-Lipschitzness
Aleksandar Petrov*, Francisco Eiras, Amartya Sanyal, Philip H.S. Torr, Adel Bibi*
ICML, 2023
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Computationally Budgeted Continual Learning: What Does Matter?
Ameya Prabhu*, Hasan Abed Al Kader Hammoud*, Puneet Dokania, Philip H.S. Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi
CVPR, 2023
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Patch-based Separable Transformer for Visual Recognition
Shuyang Sun, Xiaoyu Yue, Hengshuang Zhao, Philip HS Torr, Song Bai
AAAI, 2022
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Occluded video instance segmentation: A benchmark
Jiyang Qi, Yan Gao, Yao Hu, Xinggang Wang, Xiaoyu Liu, Xiang Bai, Serge Belongie, Alan Yuille, Philip HS Torr, Song Bai
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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Memory-Driven Text-to-Image Generation
Bowen Li, Philip HS Torr, Thomas Lukasiewicz
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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Diversified Dynamic Routing for Vision Tasks
Botos Csaba, Adel Bibi, Yanwei Li, Philip Torr, Ser-Nam Lim
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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YouMVOS: An Actor-Centric Multi-Shot Video Object Segmentation Dataset
Donglai Wei, Siddhant Kharbanda, Sarthak Arora, Roshan Roy, Nishant Jain, Akash Palrecha, Tanav Shah, Shray Mathur, Ritik Mathur, Abhijay Kemkar, Anirudh Chakravarthy, Zudi Lin, Won-Dong Jang, Yansong Tang, Song Bai, James Tompkin, Philip HS Torr, Hanspeter Pfister
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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Transmix: Attend to mix for vision transformers
Jie-Neng Chen, Shuyang Sun, Ju He, Philip HS Torr, Alan Yuille, Song Bai
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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Structure-Preserving 3D Garment Modeling with Neural Sewing Machines
Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip H. S. Torr, Liang Lin
Neural Information Processing Systems (NeurIPS), 2022
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Semantic-Aware Auto-Encoders for Self-Supervised Representation Learning
Guangrun Wang, Yansong Tang, Liang Lin, Philip HS Torr
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness
Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip Torr
European Conference on Computer Vision (ECCV), 2022
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PhysFormer: facial video-based physiological measurement with temporal difference transformer
Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip HS Torr, Guoying Zhao
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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Patch-based Separable Transformer for Visual Recognition
Shuyang Sun, Xiaoyu Yue, Hengshuang Zhao, Philip HS Torr, Song Ba
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
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Not Just Pretty Pictures: Text-to-Image Generators Enable Interpretable Interventions for Robust Representations
Jianhao Yuan, Francesco Pinto, Adam Davies, Aarushi Gupta, Philip Torr
International Journal of Computer Vision, 2022
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Make Some Noise: Reliable and Efficient Single-Step Adversarial Training
Pau de Jorge, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip H. S. Torr, Grégory Rogez, Puneet K. Dokania
NeurIPS, 2022
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Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning
Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip HS Torr, Song Bai, Vincent YF Tan
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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Local and Global GANs with Semantic-Aware Upsampling for Image Generation
Hao Tang, Ling Shao, Philip HS Torr, Niculae Sebe
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
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Learning Multimodal VAEs through Mutual Supervision
Tom Joy, Yuge Shi, , Philip H.S Torr, Tom Rainforth, Sebastian Schmon, Siddharth N
International Conference on Learning Representations (ICLR), 2022
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Large-scale Unsupervised Semantic Segmentation
Shanghua Gao, Zhong-Yu Li, Ming-Hsuan Yang, Ming-Ming Cheng, Junwei Han, Philip Torr
T-PAMI 2022
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Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detection and Spotting
Chuhui Xue, Yu Hao, Shijian Lu, Philip Torr, Song Bai
ECCV 2022
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LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip H.S. Torr
In the Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022
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KL Guided Domain Adaptation
A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, Atilim Gunes Baydin
ICLR, 2022
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Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning
Nan Xue, Tianfu Wu, Song Bai, Fu-Dong Wang, Gui-Song Xia, Liangpei Zhang, Philip HS Torr
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments
Xiaogang Xu, Hengshuang Zhao, Philip Torr, Jiaya Jia
International Journal of Computer Vision, 2022
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Estimating the Impact of Coordinated Inauthentic Behavior on Content Recommendations in Social Networks
Swapneel Mehta, Atilim Gunes Baydin, Bogdan State, Richard Bonneau, Jonathan Nagler, Philip Torr
AI for Agent-based Models Workshop, ICML; Misinfocon, DEFCON
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Dynamic Graph Message Passing Networks for Visual Recognition
Li Zhang, Mohan Chen, Anurag Arnab, Xiangyang Xue, Philip HS Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
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Diagnosing and preventing instabilities in recurrent video processing
Thomas Tanay, Aivar Sootla, Matteo Maggioni, Puneet K Dokania, Philip HS Torr, Ales Leonardis, Greg Slabaugh
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
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DeformRS: Certifying Input Deformations with Randomized Smoothing
Motasem Alfarra*, Adel Bibi*, Naeemullah Khan, Philip H. S. Torr, Bernard Ghanem
AAAI, 2022
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Data Dependent Randomized Smoothing
Motasem Alfarra*, Adel Bibi*, Philip HS Torr, Bernard Ghanem
Uncertainty in Artificial Intelligence (UAI), 2022
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Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs
Guangrun Wang, Philip HS Torr
Computer Vision and Pattern Recognition
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Clustering Generative Adversarial Networks for Story Visualization
Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz
Proceedings of the 30th ACM International Conference on Multimedia, 2022
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Bipartite Graph Reasoning GANs for Person Pose and Facial Image Synthesis
Hao Tang, Ling Shao, Philip H.S. Torr, Nicu Sebe
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
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BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion
Kejie Li, Yansong Tang, Victor Adrian Prisacariu, Philip HS Torr
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Combating Adversaries with Anti-Adversaries
Motasem Alfarra, Juan C. Pérez, Ali Thabet, Adel Bibi, Philip H. S. Torr, Bernard Ghanem
AAAI, 2022
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FedSR: A Simple and Effective Domain Generalization Method for Federated Learning
A. Tuan Nguyen, Philip H.S. Torr, Ser-Nam Lim
NeurIPS, 2022
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You Never Cluster Alone
Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip H.S. Torr, Ling Shao
NeurIPS, 2021
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Vision Transformer with Progressive Sampling
Xiaoyu Yue*, Shuyang Sun*, Zhanghui Kuang, Meng Wei, Philip Torr, Wayne Zhang, Dahua Lin
IEEE/CVF International Conference on Computer Vision (ICCV), 2021
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Using Hindsight to Anchor Past Knowledge in Continual Learning
Arslan Chaudhry, David Lopez-Paz, Albert Gordo, Puneet K. Dokania, Philip H. S. Torr
AAAI, 2021
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Understanding the effects of data parallelism and sparsity on neural network training
Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi
International Conference on Learning Representations (ICLR), 2021
[PDF] | MURI

Solving Inefficiency of Self-supervised Representation Learning
Guangrun Wang, Keze Wang, Guangcong Wang, Philip H.S. Torr, and Liang Lin
IEEE/CVF International Conference on Computer Vision (ICCV), 2021
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Shape-Tailored Deep Neural Networks With PDEs
Naeemullah Khan, Angira Sharma, Philip Torr, Ganesh Sundaramoorthi
NeurIPS, 2021
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Separable Flow: Learning Motion Cost Volumes for Optical Flow Estimation
Feihu Zhang, Oliver J. Woodford, Victor Prisacariu, Philip H.S. Torr
International Conference on Computer Vision (ICCV), 2021
[PDF] | MURI

Scaling the Convex Barrier with Active Sets
Harkirat Singh Behl, Alessandro De Palma, Rudy Bunel, Philip H.S. Torr, M. Pawan Kumar
International Conference on Learning Representations (ICLR), 2021
[PDF] | MURI

SECI-GAN: Semantic and Edge Completion for dynamic objects removal
Francesco Pinto, Andrea Romanoni, Matteo Matteucci, Philip H.S. Torr
International Conference on Pattern Recognition (ICPR), 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, Li Zhang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
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Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning
Hongguang Zhang, Piotr Koniusz, Songlei Jian, Hongdong Li, Philip HS Torr
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
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Res2Net: A New Multi-Scale Backbone Architecture
Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
[PDF] | MURI

Relating by Contrasting: A Data-efficient Framework for Multimodal DGMs
Yuge Shi, Brooks Paige, Philip H.S. Torr, N. Siddharth
International Conference on Learning Representations (ICLR), 2021
[PDF] | MURI

Progressive skeletonization: Trimming more fat from a network at initialization
Pau de Jorge, Amartya Sanyal, Harkirat S. Behl, Philip HS Torr, Gregory Rogez, and Puneet K. Dokania
International Conference on Learning Representations (ICLR), 2021
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Point Transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip Torr, Vladlen Koltun
IEEE/CVF International Conference on Computer Vision (ICCV), 2021
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Overcoming the Convex Barrier for Simplex Input
Harkirat Singh Behl, M Pawan Kumar, Philip Torr, Krishnamurthy Dvijotham
NeurIPS, 2021
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Occluded Video Instance Segmentation: Dataset and Challenge
Jiyang Qi, Yan Gao, Yao Hu, Xinggang Wang, Xiaoyu Liu, Xiang Bai, Serge Belongie, Alan Yuille, Philip Torr, Song Bai
NeurIPS, 2021
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No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania, Vineet Gandhi
International Conference on Learning Representations (ICLR), 2021
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Multi-shot Temporal Event Localization: a Benchmark
Xiaolong Liu, Yao Hu, Song Bai, Fei Ding, Xiang Bai, Philip H.S. Torr
CVPR, 2021
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Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks
Francesco Pinto, Harry Yang, Ser Nam Lim, Philip Torr, Puneet Dokania
NeurIPS, 2021
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Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania
AISTATS 2021
[PDF] | MURI

Looking Beyond Single Images for Contrastive Semantic Segmentation Learning
Feihu Zhang, Philip Torr, René Ranftl, Stephan R. Richter
NeurIPS, 2021
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Hypergraph convolution and hypergraph attention
Song Bai, Feihu Zhang, Philip HS Torr
Pattern Recognition, 2021
[PDF] | MURI

Hierarchical Interaction Network for Video Object Segmentation from Referring Expressions
Zhao Yang, Yansong Tang, Luca Bertinetto, Hengshuang Zhao, Philip H.S. Torr
In the Proceedings of the British Machine Vision Conference (BMVC) 2021
[PDF]

FACMAC: Factored Multi-Agent Centralised Policy Gradients
Bei Peng, Tabish Rashid, Christian Schroeder de Witt, Pierre-Alexandre Kamienny, Philip Torr, Wendelin Böhmer, Shimon Whiteson
NeurIPS, 2021
[PDF]

Domain Invariant Representation Learning with Domain Density Transformations
A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin
NeurIPS, 2021
[PDF]

Do Different Tracking Tasks Require Different Appearance Models?
Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip H.S. Torr, Luca Bertinetto
NeurIPS, 2021
[PDF]

Deep learning for predicting COVID-19 malignant progression
Cong Fang, Song Bai, Qianlan Chen, Yu Zhoua, Liming Xia, Lixin Qin, Shi Gong, Xudong Xie, Chunhua Zhou, Dandan Tu, Changzheng Zhang, Xiaowu Liu, Weiwei Chen, Xiang Bai, Philip H.S.Torr
Medical Image Analysis, Volume 72, August 2021, 102096
[PDF] | MURI

Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation
Angira Sharma, Naeemullah Khan, Muhammad Mubashar, Ganesh Sundaramoorthi, Philip Torr
IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021
[PDF]

Capturing Label Characteristics in VAEs
Tom Joy, Sebastian Schmon, Philip Torr, Siddharth N, Tom Rainforth
International Conference on Learning Representations (ICLR), 2021
[PDF]

AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks
Hao Tang, Hong Liu, Dan Xu, Philip H.S. Torr, Nicu Sebe
IEEE Transactions on Neural Networks and Learning Systems 2021
[PDF] | MURI

Are Vision Transformers Always More Robust Than Convolutional Neural Networks?
Francesco Pinto, Philip Torr, Puneet Dokania
NeurIPS, 2021
[PDF]

Aggregation with Feature Detection
Shuyang Sun, Xiaoyu Yue, Xiaojuan Qi, Wanli Ouyang, Victor Prisacariu, Philip Torr
IEEE/CVF International Conference on Computer Vision (ICCV), 2021
[PDF] | MURI

A Continuous Mapping For Augmentation Design
Keyu Tian, Chen Lin, Ser Nam Lim, Wanli Ouyang, Puneet Dokania, Philip Torr
NeurIPS, 2021
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XingGAN for Person Image Generation
Hao Tang, Song Bai, Li Zhang, Philip H.S. Torr, Nicu Sebe
European Conference on Computer Vision 2020
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Unifying Training and Inference for Panoptic Segmentation
Qizhu Li, Xiaojuan Qi, Philip H.S. Torr
Computer Vision and Pattern Recognition 2020
[PDF] | MURI

Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal, Puneet Kumar Dokania, Philip H.S. Torr
International Conference on Learning Representations 2020
[PDF] | MURI

Spatio-Temporal Action Instance Segmentation and Localisation
Suman Saha, Gurkit Singh, Michael Sapienza, Philip H.S. Torr, Fabio Cuzzolin
2017 Modelling Human Motion: From Human Perception to Robot Design, Pages:141-161
[PDF]

Simulation-Based Inference for Global Health Decisions
Christian Schroeder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Rob Zinkov, Puneet Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip Torr, Atılım Günes Baydin
ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)
[PDF] | MURI

Siam R-CNN:Visual Tracking by Re-Detection
Paul Voigtlaender, Jonathon Luiten, Philip H.S. Torr, Bastian Leibe
Computer Vision and Pattern Recognition 2020
[PDF] | MURI

Scalable FPGA Median Filtering using Multiple Efficient Passes
Oscar Rahnama, Tommaso Cavallari, Philip H. S. Torr, Stuart Golodetz
FPGA '20: Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays
[PDF] | MURI

STEER: Simple Temporal Regularization For Neural ODEs
Arnab Ghosh, Harkirat Singh Behl, Emilien Dupont, Philip H. S. Torr, Vinay Namboodiri
Neurips 2020
[PDF] | MURI

Real-Time RGB-D Camera Pose Estimation in Novel Scenes Using a Relocalisation Cascade
Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord, Julien Valentin, Victor A. Prisacariu, Luigi Di Stefano, Philip H. S. Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence (Volume: 42, Issue: 10, Oct. 1 2020)
[PDF] | MURI

On using Focal Loss for Neural Network Calibration
Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip H.S. Torr, Puneet Kumar Dokania
ICML Uncertainty and Robustness in Deep Learning (UDL) workshop 2020
[PDF] | MURI

Multitask Soft Option Learning
Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N. Siddharth, Wendelin Bohmer, Shimon Whiteson
Uncertainty in Artificial Intelligence 2019
[PDF] | MURI

Meta Learning Deep Visual Words for Fast Video Object Segmentation
Harkirat Singh Behl, Mohammad Najafi, Anurag Arnab, Philip H.S. Torr
International Conference on Intelligent Robots and Systems (IROS) 2020
[PDF]

ManiGAN:Text-Guided Image Manipulation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H.S. Torr
Computer Vision and Pattern Recognition 2020
[PDF] | MURI

Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
Hao Tang, Dan Xu, Yan Yan, Philip H.S. Torr, Nicu Sebe
Computer Vision and Pattern Recognition 2020
[PDF]

Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation
Bowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz
Neural Information Processing Systems 2020
[PDF]

Lessons from Reinforcement Learning for Biological Representations of Space
Alex Muryy, N. Siddharth, Nantas Nardelli, Andrew Glennerster, Philip H.S. Torr
2020 Vision Research
[PDF] | MURI

Learning Generative Models from Classifier Uncertainties
N. Siddharth, Brooks Paige
ICML Workshop on Uncertainty & Robustness in Deep Learning
[PDF] | MURI

Lagrangian Decomposition for Neural Network Verification
Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H.S. Torr, M Pawan Kumar
Conference on Uncertainty in Artificial Intelligence 2020
[PDF]

Instance Segmentation of LiDAR Point Clouds
Feihu Zhang, Chenye Guan, Jin Fang, Song Bai, Ruigang Yang, Philip H.S. Torr, Victor Adrian Prisacariu
IEEE International Conference on Robotics and Automation 2020
[PDF] | MURI

Holistically-Attracted Wireframe Parsing
Tianfu Wu, Nan Xue, Song Bai, Fudong Wang, Gui-Song Xia, Liangpei Zhang, Philip H.S. Torr
Computer Vision and Pattern Recognition 2020
[PDF] | MURI

HOTA:A Higher Order Metric for Evaluating Multi-object Tracking
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip H.S. Torr, Andreas Geiger, Laura Lealtaixe, Bastian Leibe
International Journal of Computer Vision (2020)
[PDF]

GDumb:A Simple Approach that Questions Our Progress in Continual Learning
Ameya Prabhu, Puneet Kumar Dokania, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2020
[PDF] | MURI

Dynamic Graph Message Passing Network
Li Zhang, Dan Xu, Anurag Arnab, Philip H.S. Torr
Computer Vision and Pattern Recognition 2020
[PDF] | MURI

Domain-invariant Stereo Matching Networks
Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Adrian Prisacariu, Benjamin Wah, Philip H.S. Torr
European Conference on Computer Vision (ECCV), 2020
[PDF] | MURI

Deep Probabilistic Surrogate Networks for Universal Simulator Approximation
Andreas Munk, Adam Scibior, Atılım Gunes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood
International Conference on Probabilistic Programming (PROBPROG 2020)
[PDF] | MURI

Deep FusionNet for Point Cloud Semantic Segmentation
Feihu Zhang, Jin Fang, Benjamin Wah, Philip H.S. Torr
European Conference on Computer Vision (ECCV), 2020
[PDF] | MURI

Data Parallelism in Training Sparse Neural Networks
Namhoon Lee, Philip H.S. Torr, Martin Jaggi
ICLR 2020 Workshop on PML4DC: Learning under limited/low resource scenarios
[PDF] | MURI

DGPose:Deep Generative Models for Human Body Analysis
Rodrigo de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik*, Adnane Boukhayma, N. Siddharth, Philip H.S. Torr
International Journal of Computer Vision (2020) 128:1537–1563
[PDF] | MURI

Cross-modal Deep Face Normals with Deactivable Skip Connections
Victoria Fernandez Abrevaya, Adnane Boukhayma, Philip H.S. Torr, Edmond Boyer
Computer Vision and Pattern Recognition 2020
[PDF] | MURI

Continual Learning in Low-rank Orthogonal Subspaces
Arslan Chaudhry, Naeemullah Khan, Puneet Kumar Dokania, Philip H.S. Torr
Neural Information Processing Systems 2020
[PDF]

Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip H. S. Torr, Puneet K. Dokania
Advanced in Neural Information Processing Systems, 2020
[PDF]

Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation
Viveka Kulharia, Siddhartha Chandra, Amit Agrawal, Philip Torr, Ambrish Tyagi
Computer Vision – ECCV 2020
[PDF] | MURI

Black-Box Optimization with Local Generative Surrogates
Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atılım Güne¸s Baydin
Neural Information Processing Systems (NeurIPS 2020)
[PDF] | MURI

Bipartite Graph Reasoning GANs for Person Image Generation
Hao Tang, Song Bai, Philip H.S. Torr, Nicu Sebe
British Machine Vision Conference 2020
[PDF]

AutoSimulate:(Quickly) Learning Synthetic Data Generation
Harkirat Singh Behl, Atılım Güneş Baydin , Ran Gal, Philip H.S. Torr, Vibhav Vineet
European Conference on Computer Vision (ECCV)
[PDF]

Attention for Inference Compilation
William Harvey, Andreas Munk, Atılım Güneş Baydin, Alexander Bergholm, Frank Wood
International Conference on Probabilistic Programming (PROBPROG 2020)
[PDF] | MURI

An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval
Adam Cobb, Michael Himes, Frank Soboczenski, Simone Zorzan, Molly Obeirne, Atılım Güneş Baydin , Yarin Gal, Shawn Domagal-Goldman, Giada Arney, Daniel Angerhausen
The Astronomical Journal 158 (1). doi:10.3847/1538-3881/ab2390
[PDF] | MURI

Amortized Rejection Sampling in Universal Probabilistic Programming
Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atılım Gunes Baydin, Bradley Gram-Hansen, Christian Schroeder de Witt, Robert Zinkov, Philip H.S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
International Conference on Probabilistic Programming (PROBPROG 2020)
[PDF] | MURI

Adversarial Metric Attack and Defense for Person Re-identification
Song Bai, Yingwei Li, Yuyin Zhou, Qizhu Li, and Philip H.S. Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
[PDF] | MURI

A Signal Propagation Perspective for Pruning Neural Networks at Initialization
Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H.S. Torr
International Conference on Learning Representations 2020
[PDF] | MURI

Few-Shot Action Recognition with Permutation-Invariant Attention
Hongguang Zhang, Li Zhang, Xiaojuan Qi, Hongdong Li, Philip H. S. Torr, Piotr Koniusz
Computer Vision – ECCV 2020
[PDF] | MURI

Video Segmentation by Detection for the 2019 Unsupervised DAVIS Challenge
Zhao Yang, Qiang Wang, Song Bai, Weiming Hu, Philip H.S. Torr
The 2019 DAVIS Challenge on Video Object Segmentation - CVPR Workshops 2019
[PDF] | MURI

Video Instance Segmentation 2019:A winning approach for combined Detection Segmentation Classification and Tracking
Jonathon Luiten, Philip H.S. Torr, Bastian Leibe
The 2nd Large-scale Video Object Segmentation Challenge: International Conference on Computer Vision Workshop (ICCVW)
[PDF] | MURI

Variational Mixture of Experts Autoencoders for Multi-Modal Deep Generative Models
Yuge (Jimmy) Shi, N. Siddharth, Brooks Paige, Philip H.S. Torr
Neural Information Processing Systems 2019
[PDF] | MURI

Value Propagation Networks
Nantas Nardelli, Zeming Lin, Pushmeet Kohli, Philip H.S. Torr, Nicolas Usunier
International Conference on Learning Representations (ICLR) 2019
[PDF] | MURI

Structured Disentangled Representations
Babak Esmaeili, Hao Wu, Sarthak Jain, N. Siddharth, Brooks Paige, Dana H. Brooks, Jennifer Dy, Jan-Willem van de Meent
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)
[PDF] | MURI

Stable Rank Normalization for Improved Generalization in Neural Networks
Amartya Sanyal, Philip H.S. Torr, Puneet Kumar Dokania
In the proceedings of the International Conference on Machine Learning (ICML) Workshop Understanding and Improving Generalization in Deep Learning 2019
[PDF] | MURI

Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training
Yuyin Zhou, Yan Wang, Peng Tang, Song Bai, Wei Shen, Elliot K. Fishman, Alan Yuille
IEEE Winter Conference on Applications of Computer Vision (WACV)
[PDF] | MURI

SNIP:Single-shot Network Pruning Based On Connection Sensitivity
Namhoon Lee, Thalaiyasingam Ajanthan, Philip H.S. Torr
International Conference on Learning Representations (ICLR) 2019
[PDF] | MURI

Robust Multi-Modality Multi-Object Tracking
Wenwei Zhang, Hui Zhou, Shuyang Sun, Zhe Wang, Jianping Shi, Chenchange Loy
ICCV
[PDF] | MURI

Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood
Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI) Tel Aviv Israel
[PDF] | MURI

Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification
Song Bai, Peng Tang, Philip H.S. Torr, Longin Jan Latecki
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Proximal Mean-field for Neural Network Quantization
Thalaiyasingam Ajanthan, Puneet Kumar Dokania, R. Hartley, Philip H.S. Torr
International Conference on Computer Vision 2019
[PDF] | MURI

PCL:Proposal Cluster Learning for Weakly Supervised Object Detection
Peng Tang, Xinggang Wang, Song Bai, Wei Shen, Xiang Bai, Wenyu Liu, Alan Yuille
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
[PDF] | MURI

On Tiny Episodic Memories in Continual Learning
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H.S. Torr, Marc'Aurelio Ranzato
International Conference on Machine Learning (ICML) Multi-Task and Lifelong Reinforcement Learning Workshop 2019
[PDF] | MURI

Multi-Agent Common Knowledge Reinforcement Learning
Christian Schroeder de Witt, Jakob Foerster*, Gregory Farquhar, Philip H.S. Torr, Wendelin Boehmer, Shimon Whiteson
Advances in Neural Information Processing Systems 9924-9935
[PDF] | MURI

Meta-learning with differentiable closed-form solvers
Luca Bertinetto, João F. Henriques, Philip H.S. Torr, Andrea Vedaldi
International Conference on Learning Representations (ICLR) 2019
[PDF] | MURI

Meta Learning Deep Visual Words for Fast Video Object Segmentation
Harkirat Singh Behl, Mohammad Najafi, Anurag Arnab, Philip H.S. Torr
Neural Information Processing Systems Machine Learning for Autonomous Driving Workshop 2019
[PDF] | MURI

Let's Take This Online:Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Tommaso Cavallari*, Luca Bertinetto, Jishnu Mukhoti, Philip H.S. Torr, Stuart Golodetz*
International Conference on 3D Vision (3DV) 2019
[PDF] | MURI

Learning To Adapt For Stereo
Alessio Tonioni, Oscar Rahnama, Thomas Joy, Luigi Di Stefano, Thalaiyasingam Ajanthan, Philip H.S. Torr
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Learning Regional Attraction for Line Segment Detection
Nan Xue, Song Bai, Fudong Wang, Gui-Song Xia, Tianfu Wu, Liangpei Zhang, Philip H.S. Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2020
[PDF] | MURI

Learning Attraction Field Representation for Robust Line Segment Detection
Nan Xue, Song Bai, Fudong Wang, Gui-Song Xia, Tianfu Wu, Liangpei Zhang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Interactive Sketch & Fill:Multiclass Sketch-to-Image Translation
Arnab Ghosh, Richard Zang, Puneet Kumar Dokania, Oliver Wang, Alexei Efros, Philip H.S. Torr, Eli Shechtman
International Conference on Computer Vision 2019
[PDF] | MURI

GA-Net:Guided Aggregation Net for End-to-end Stereo Matching
Feihu Zhang, Victor Adrian Prisacariu, Ruigang Yang, Philip H.S. Torr
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Fast Online Object Tracking and Segmentation:A Unifying Approach
Qiang Wang, Li Zhang, Luca Bertinetto, Weiming Hu, Philip H.S. Torr
Computer Vision and Pattern Recognition 2019
[PDF] | MURI

Exploiting Temporal Context for 3D Human Pose Estimation in the Wild
Anurag Arnab, Carl Doersch, Andrew Zisserman
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Etalumis:Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin , Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Mingfei Ma, Philip H.S. Torr, Victor Lee, Kyle Cranmer, Prabhat, Frank Wood
Proceedings of the International Conference for High Performance Computing Networking Storage and Analysis (SC19)
[PDF] | MURI

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials
Thomas Joy, Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H.S. Torr, M Pawan Kumar
SIAM J. Imaging Sciences 12(1): 287-318
[PDF] | MURI

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Philip H.S. Torr, Lawrence Meadows, Atılım Güneş Baydin , Lukas Heinrich, Wahid Bhimji, Lei Shao, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Philip H.S. Torr, Victor Lee, Prabhat, Kyle Cranmer, Frank Wood
Advances in Neural Information Processing Systems 33 (NeurIPS)
[PDF] | MURI

Efficient Lifelong Learning with A-GEM
Arslan Chaudhry, Marc'Aurelio Ranzato, Marcus Rohrbach, Mohamed Elhoseiny
International Conference on Learning Representations (ICLR)
[PDF] | MURI

Dual Graph Convolutional Network for Semantic Segmentation
Li Zhang, Xiangtai Li, Anurag Arnab, Kuiyuan Yang, Yunhai Tong, Philip H.S. Torr
British Machine Vision Conference 2019
[PDF] | MURI

Disentangling Disentanglement in Variational Autoencoders
Emile Mathieu, Tom Rainforth, N. Siddharth, Yee Whye Teh
Proceedings of the International Conference on Machine Learning (ICML) 2019 Long Beach CA June 2019
[PDF] | MURI

Deeply Supervised Salient Object Detection with Short Connections.
Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, Philip H.S. Torr
IEEE Trans. Pattern Anal. Mach. Intell. 41(4): 815-828
[PDF] | MURI

Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks
Eunwoo Kim, Chanho Ahn, Philip H.S. Torr, Songhwai Oh
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Controllable Text-to-Image Generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H.S. Torr
Neural Information Processing Systems 2019
[PDF] | MURI

BING:Binarized normed gradients for objectness estimation at 300fps
Ming-Ming Cheng, Yun Liu, Wenyu Liu, Ziming Zang, Paul L. Rosin,, Philip H.S. Torr
Computational Visual Media 5(1): 3-20
[PDF] | MURI

Anchor Diffusion for Unsupervised Video Object Segmentation
Zhao Yang, Qiang Wang, Luca Bertinetto, Weiming Hu, Song Bai, Philip H.S. Torr
International Conference on Computer Vision 2019
[PDF] | MURI

Alpha MAML:Adaptive Model-Agnostic Meta-Learning
Harkirat Singh Behl, Atılım Güneş Baydin , Philip H.S. Torr
6th ICML Workshop on Automated Machine Learning Thirty-Sixth International Conference on Machine Learning (ICML)
[PDF] | MURI

A Decoupled 3D Facial Shape Model by Adversarial Training
Victoria Fernandez Abrevaya, Adnane Boukhayma, Stefanie Wuhrer, Edmond Boyer
International Conference on Computer Vision 2019
[PDF] | MURI

A Conditional Deep Generative Model of People in Natural Images
Rodrigo de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, N. Siddharth, Philip H.S. Torr, Adnane Boukhayma
To appear in Winter Conference on Applications of Computer Vision (WACV) 2019
[PDF] | MURI

3d Hand Shape and Pose from Images in the Wild
Adnane Boukhayma, Rodrigo de Bem, Philip H.S. Torr
Computer Vision and Pattern Recognition 2019
[PDF] | MURI

With Friends Like These Who Needs Adversaries?
Saumya Jetley*, Nicholas A. Lord*, Philip H.S. Torr
Neural Information Processing Systems (NeurIPS) 2018
[PDF] | MURI

Weakly- and Semi-Supervised Panoptic Segmentation
Qizhu Li, Anurag Arnab, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2018
[PDF] | MURI

Visual Dialogue without Vision or Dialogue
Puneet Kumar Dokania, Philip H.S. Torr, N. Siddharth, Daniela Massiceti
NeurIPS 2018 workshop on Critiquing and Correcting Trends in Machine Learning
[PDF] | MURI

Similarity Learning for Dense Label Transfer
Mohammad Najafi, Viveka Kulharia, Thalaiyasingam Ajanthan, Philip H.S. Torr
The 2018 DAVIS Challenge on Video Object Segmentation - CVPR Workshops
[PDF]

Riemannian Walk for Incremental Learning:Understanding Forgetting and Intransigence
Arslan Chaudhry, Puneet Kumar Dokania, Thalaiyasingam Ajanthan, Philip H.S. Torr, Arslan Chaudhry, Puneet Kumar Dokania, Thalaiyasingam Ajanthan, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2018
[PDF] | MURI

Revisiting Deep Structured Models for Pixel-Level Labeling with Gradient-Based Inference
Mans Larsson, Anurag Arnab, Shuai Zheng, Philip H.S. Torr, Fredrik Kahl
SIAM J. Imaging Sciences (Society for Industrial and Applied Mathematics) vol. 11 no. 4 pp. 2610-2628 2018
[PDF] | MURI

Real-Time Dense Stereo Matching with ELAS on FPGA Accelerated Embedded Devices
Oscar Rahnama, Duncan Frost, Philip H.S. Torr, Ondrej Miksik
IEEE Robotics and Automation Letters (RA-L)
[PDF] | MURI

R3SGM:Real-time Raster-Respecting Semi-Global
Oscar Rahnama, Tommaso Cavallari*, Stuart Golodetz*, Simon Walker, Philip H.S. Torr
International Conference on Field-Programmable Technology (FPT) 2018
[PDF] | MURI

QMIX:Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder de Witt, Gregory Farquhar, Jakob Foerster, Shimon Whiteson
In Proceedings International Conference of Machine Learning (ICML) 2018
[PDF] | MURI

On the Robustness of Semantic Segmentation Models to Adversarial Attacks
Anurag Arnab, Ondrej Miksik, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Multi-Agent Diverse Generative Adversarial Networks
Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri, Arnab Ghosh, Philip H.S. Torr, Puneet Kumar Dokania
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Long-term Tracking in the Wild:A Benchmark
Jack Valmadre, Luca Bertinetto, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold W. M. Smeulders, Philip H.S. Torr, Efstratios Gavves
European Conference on Computer Vision (ECCV) 2018
[PDF] | MURI

Learning to Compare:Relation Network for Few-Shot Learning
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H.S. Torr, Timothy M Hospedales
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018
[PDF] | MURI

Learn To Pay Attention
Saumya Jetley, Nicholas A. Lord, Namhoon Lee, Philip H.S. Torr
International Conference on Learning Representations (ICLR)
[PDF] | MURI

Incremental Tube Construction for Human Action Detection
Harkirat Singh Behl, Michael Sapienza, Gurkirt Singh, Suman Saha, Fabio Cuzzolin, Philip H.S. Torr
In the Proceedings of the British Machine Vision Conference (BMVC) 2018
[PDF] | MURI

FlipDial:A Generative Model for Two-Way Visual Dialogue
Daniela Massiceti, N. Siddharth, Puneet Kumar Dokania, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Faithful inversion of generative models for effective amortized inference
Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Tom Rainforth, Yee Whye Teh, Frank Wood
Neural Information Processing Systems (NeurIPS) 2018
[PDF] | MURI

Disentangling Disentanglement
Emile Mathieu, Tom Rainforth, N. Siddharth, Yee Whye Teh
NeurIPS Workshop on Bayesian Deep Learning
[PDF] | MURI

Devon:Deformable Volume Network for Learning Optical Flow
Yao Lu, Jack Valmadre, Heng Wang, Juho Kannala, Mehrtash Harandi, Philip H.S. Torr
European Conference on Computer Vision (ECCV) workshop 2018
[PDF] | MURI

Deep Fully-Connected Part-Based Models for Human Pose Estimation
Rodrigo de Bem, Anurag Arnab, Stuart Golodetz, Michael Sapienza, Philip H.S. Torr
Asian Conference on Machine Learning (ACML) 2018
[PDF] | MURI

Counterfactual Multi-Agent Policy Gradients
Jakob Foerster*, Gregory Farquhar*, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson
In the Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)
[PDF] | MURI

Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation
Anurag Arnab*, Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Mans Larsson, Alexander Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H.S. Torr
IEEE Signal Processing Magazine 2018
[PDF] | MURI

Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation
Stuart Golodetz, Tommaso Cavallari, Nicholas A. Lord, Victor Adrian Prisacariu, David W. Murray, Philip H.S. Torr
IEEE Transactions on Visualization and Computer Graphics (TVCG) 24(11) 2018
[PDF] | MURI

Certification of Highly Automated Vehicles for Use on UK Roads:Creating An Industry-Wide Framework for Safety
FiveAI Ltd
FiveAI Ltd Certification Paper
[PDF]

CODE:Coherence Based Decision Boundaries for Feature Correspondence
Wen-Yan Lin, Fan Wang, Ming-Ming Cheng, Sai-Kit Yeung, Philip H.S. Torr, Minh N. Do, Jiangbo Lu
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2017
[PDF] | MURI

A unified view of Piecewise Linear Neural Network Verification
Rudy Bunel, Ilker Turkaslan, Philip H.S. Torr, Pushmeet Kohli, M Pawan Kumar
Neural Information Processing Systems (NeurIPS) 2018
[PDF] | MURI

A Semi-supervised Deep Generative Model for Human Body Analysis
Rodrigo de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H.S. Torr
European Conference on Computer Vision (ECCV) HBUGEN Workshop 2018
[PDF] | MURI

Straight to Shapes:Real-time Detection of Encoded Shapes
Saumya Jetley, Michael Sapienza, Stuart Golodetz, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster*, Nantas Nardelli*, Gregory Farquhar, Philip H.S. Torr, Pushmeet Kohli, Shimon Whiteson, Triantafyllos Afouras, Triantafyllos Afouras
In the proceedings of the International Conference on Machine Learning (ICML), 2017
[PDF] | MURI

Sequential Optimization for Efficient High-Quality Object Proposal Generation.
Ziming Zhang, Yun Liu, Xi Chen, Yanyun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, Philip H.S. Torr
IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2017
[PDF] | MURI

Random Forests versus Neural Networks - What's Best for Camera Localization?
Daniela Massiceti, Alexander Krull, Eric Brachmann, Carsten Rother, Philip H.S. Torr
IEEE Conference on Robotics & Automation (ICRA) 2017
[PDF] | MURI

ROAM:a Rich Object Appearance Model with Application to Rotoscoping
Ondrej Miksik*, Juan-Manuel Perez-Rua*, Philip H.S. Torr, Patrick Perez
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

Pixelwise Instance Segmentation with a Dynamically Instantiated Network
Anurag Arnab, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

Online Real-time Multiple Spatiotemporal Action Localisation and Prediction
Gurkirt Singh, Suman Saha, Michael Sapienza, Philip H.S. Torr, Fabio Cuzzolin
IEEE International Conference on Computer Vision (ICCV), 2017
[PDF] | MURI

On-the-Fly Adaptation of Regression Forests for Online Camera Relocalisation
Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord, Julien Valentin, Luigi Di Stefano, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

Learning to superoptimize programs
Rudy Bunel, Alban Desmaison, M Pawan Kumar, Philip H.S. Torr, Pushmeet Kohli
International Conference on Learning Representations (ICLR), 2017
[PDF] | MURI

Learning Disentangled Representations with Semi-Supervised Deep Generative Models
N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank Wood, Philip H.S. Torr
Neural Information Processing Systems (NIPS), 2017
[PDF] | MURI

Holistic, Instance-level Human Parsing
Qizhu Li, Anurag Arnab, Philip H.S. Torr
In the Proceedings of the British Machine Vision Conference (BMVC), 2017
[PDF] | MURI

End-to-end representation learning for Correlation Filter based tracking
Jack Valmadre*, Luca Bertinetto*, João F. Henriques, Andrea Vedaldi, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

Efficient Minimization of Higher Order Submodular Functions using Monotonic Boolean Functions
Srikumar Ramalingam, Chris Russell, Lubor Ladicky, Philip H.S. Torr, Chris Russell, Lubor Ladicky, Philip H.S. Torr
Discrete Applied Mathematics
[PDF] | MURI

Efficient Linear Programming for Dense CRFs
Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H.S. Torr, M Pawan Kumar
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation
Arslan Chaudhry, Puneet Kumar Dokania, Philip H.S. Torr
In the Proceedings of the British Machine Vision Conference (BMVC), 2017
[PDF] | MURI

Deeply Supervised Salient Object Detection with Short Connections
Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

DESIRE:Distant Future Prediction in Dynamic Scenes with Interacting Agents
Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B. Choy, Philip H.S. Torr, Manmohan Chandraker
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] | MURI

A Projected Gradient Descent Method for CRF Inference allowing End-To-end Training of Arbitrary Pairwise Potentials
Mans Larsson, Anurag Arnab, Fredrik Kahl, Shuai Zheng, Philip H.S. Torr
Energy Minimization Methods in Computer Vision and Pattern Recognition, (EMMCVPR)
[PDF] | MURI

Staple:Complementary Learners for Real-Time Tracking
Luca Bertinetto, Jack Valmadre, Stuart Golodetz, Ondrej Miksik, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (IEEE CVPR)
[PDF]

Recurrent Instance Segmentation
Bernardino Romera-Paredes, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2016
[PDF]

Learning to superoptimize programs - Workshop version
Rudy Bunel, Alban Desmaison, M Pawan Kumar, Philip H.S. Torr, Pushmeet Kohli
Neural Abstract Machines & Program Induction (NAMPI) workshop at NIPS 2016
[PDF]

Learning to Navigate the Energy Landscape
Julien Valentin, Matthias Niessner, Angela Dai, Matthias Niessner, Pushmeet Kohli, Philip H.S. Torr, Shahram Izadi
International Conference on 3D Vision (3DV) 2016
[PDF]

Learning feed-forward one-shot learners
Luca Bertinetto*, João F. Henriques*, Jack Valmadre*, Philip H.S. Torr, Andrea Vedaldi
Neural Information Processing Systems (NIPS), 2016
[PDF]

Large-scale Binary Quadratic Optimization Using Semidefinite Relaxation and Applications
Peng Wang, Chunhua Shen, Anton van den Hengel, Philip H.S. Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence.
[PDF]

Knowing Who To Listen To:Prioritizing Experts from a Diverse Ensemble for Attribute Personalization
Shrenik Lad, Bernardino Romera-Paredes, Julien Valentin, Philip H.S. Torr, Devi Parikh
IEEE International Conference on Image Processing (ICIP) 2016
[PDF]

Joint Training of Generic CNN-CRF Models with Stochastic Optimization
Alexander Kirillov, Dmitrij Schlesinger, Shuai Zheng, Bogdan Savchynskyy, Philip H.S. Torr, Carsten Rother
Asian Conference on Computer Vision (ACCV) 2016
[PDF]

Higher Order Conditional Random Fields in Deep Neural Networks
Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2016
[PDF]

Heterogeneous Wireless System Testbed for Remote Image Processing in Automated Vehicles
Cristian Roman, Michael Sapienza, Shumao Ou, Fabio Cuzzolin, Philip H.S. Torr
IEEE/IET International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) 2016
[PDF]

HFS:Hierarchical Feature Selection for Efficient Image Segmentation
Ming-Ming Cheng, Yun Liu, Qibin Hou, Jiawang Bian, Philip H.S. Torr, Shi-Min Hu, Zhuowen Tu
European Conference on Computer Vision (ECCV) 2016
[PDF]

Fully-convolutional siamese networks for object tracking
Luca Bertinetto*, Jack Valmadre*, João F. Henriques*, Andrea Vedaldi, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2016 - workshops
[PDF]

Fully-Trainable Deep Matching
James Thewlis, Shuai Zheng, Philip H.S. Torr, Andrea Vedaldi
British Machine Vision Conference (BMVC) 2016
[PDF]

End-to-End Saliency Mapping via Probability Distribution Prediction
Saumya Jetley, Naila Murray, Eleonora Vig
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] | MURI

Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference
Peng Wang, Chunhua Shen, Anton van den Hengel, Philip H.S. Torr
International Journal of Computer Vision (IJCV)
[PDF]

Efficient Continuous Relaxations for Dense CRF
Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H.S. Torr, M Pawan Kumar
European Conference on Computer Vision (ECCV) 2016
[PDF]

Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos
Suman Saha, Gurkirt Singh, Michael Sapienza, Philip H.S. Torr, Fabio Cuzzolin
British Machine Vision Conference (BMVC) 2016
[PDF]

Coarse-to-fine Planar Regularization for Dense Monocular Depth Estimation
Stephan Liwicki, Christopher Zach, Ondrej Miksik, Philip H.S. Torr
European Conference on Computer Vision (ECCV) 2016
[PDF]

Bottom-up Instance Segmentation using Deep Higher-Order CRFs
Anurag Arnab, Philip H.S. Torr
British Machine Vision Conference (BMVC) 2016
[PDF]

Adaptive Neural Compilation
Rudy Bunel, Alban Desmaison, Pushmeet Kohli, Philip H.S. Torr, M Pawan Kumar
Advances in Neural Information Processing Systems (NIPS), 2016
[PDF]

Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices
Olaf Kaehler, Victor Adrian Prisacariu, Carl Yuheng Ren, Xin Sun, Philip H.S. Torr, David W. Murray
IEEE Transactions on Visualization and Computer Graphics
[PDF]

The Semantic Paintbrush:Interactive 3D Mapping and Recognition in Large Outdoor Spaces
Vibhav Vineet, Ondrej Miksik, Morten Lidegaard, Ram Prasaath, Matthias Niessner, Stuart Golodetz, Stephen Hicks, Patrick Perez, Shahram Izadi, Philip H.S. Torr
Proceedings of the 33nd annual ACM conference on Human factors in computing systems (CHI)
[PDF]

Target Identity-aware Network Flow for Online Multiple Target Tracking
Afshin Dehghan, Yicong Tian, Philip H.S. Torr, Mubarak Shah
IEEE International Conference on Computer Vision and Pattern Recognition (IEEE CVPR)
[PDF]

Struck:Structured Output Tracking with Kernels.
Sam Hare, Stuart Golodetz, Amir Saffari, Vibhav Vineet, Ming-Ming Cheng, Stephen Hicks, Philip H.S. Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015
[PDF]

SemanticPaint:Interactive Segmentation and Learning of 3D Worlds
Stuart Golodetz, Michael Sapienza, Julien Valentin, Vibhav Vineet, Ming-Ming Cheng, Victor Adrian Prisacariu, Olaf Kaehler, Carl Yuheng Ren, Anurag Arnab, Stephen Hicks, David W. Murray, Shahram Izadi, Philip H.S. Torr
Proceeding ACM SIGGRAPH 2015 Emerging Technologies
[PDF]

SemanticPaint:Interactive 3D Labeling and Learning at your Fingertips
Julien Valentin, Vibhav Vineet, Ming-Ming Cheng, David Kim, Jamie Shotton, Pushmeet Kohli, Matthias Niessner, Antonio Criminisi, Shahram Izadi, Philip H.S. Torr
ACM Transactions on Graphics
[PDF]

SemanticPaint:A Framework for the Interactive Segmentation of 3D Scenes
Stuart Golodetz, Michael Sapienza, Julien Valentin, Vibhav Vineet, Ming-Ming Cheng, Anurag Arnab, Victor Adrian Prisacariu, Olaf Kaehler, Carl Yuheng Ren, David W. Murray, Shahram Izadi, Philip H.S. Torr
arXiv
[PDF]

Prototypical Priors:From Improving Classification to Zero-Shot Learning
Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip H.S. Torr
British Machine Vision Conference (BMVC)
[PDF]

Object Proposal Estimation in Depth Images using Compact 3D Shape Manifolds
Shuai Zheng, Victor Adrian Prisacariu, Melinos Averkiou, Ming-Ming Cheng, Niloy J. Mitra, Jamie Shotton, Philip H.S. Torr, Carsten Rother
German Conference on Pattern Recognition (GCPR)
[PDF]

Joint Object-Material Category Segmentation from Audio-Visual Cues
Anurag Arnab, Michael Sapienza, Stuart Golodetz, Julien Valentin, Ondrej Miksik, Shahram Izadi, Philip H.S. Torr
British Machine Vision Conference (BMVC)
[PDF]

Incremental Dense Semantic Stereo Fusion for Large-Scale Semantic Scene Reconstruction
Vibhav Vineet, Ondrej Miksik, Morten Lidegaard, Matthias Niessner, Stuart Golodetz, Victor Adrian Prisacariu, Olaf Kaehler, David W. Murray, Shahram Izadi, Patrick Perez, Philip H.S. Torr
IEEE International Conference on Robotics and Automation (ICRA)
[PDF]

Incremental Dense Multi-modal 3D Scene Reconstruction
Ondrej Miksik, Vibhav Vineet, Patrick Perez, Philip H.S. Torr
IEEE/RSJ International Conference on Intelligent Robots and Systems
[PDF]

Exploiting Uncertainty in Regression Forests for Accurate Camera Relocalization
Julien Valentin, Matthias Niessner, Jamie Shotton, A.W. Fitzgibbon, Shahram Izadi, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (IEEE CVPR)
[PDF]

DenseCut:Densely Connected CRFs for Realtime GrabCut
Ming-Ming Cheng, Victor Adrian Prisacariu, Shuai Zheng, Philip H.S. Torr, Carsten Rother
Computer Graphics Forum
[PDF]

Conditional Random Fields as Recurrent Neural Networks
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H.S. Torr
IEEE International Conference on Computer Vision (IEEE ICCV) 2015
[PDF]

An embarrassingly simple approach to zero-shot learning
Bernardino Romera-Paredes, Philip H.S. Torr
Proceedings of The 32nd International Conference on Machine Learning (ICML)
[PDF]

Semantic Mapping of Road Scenes
Sunando Sengupta
Department of Computing, Oxford Brookes University
[PDF]

Probabilistic Models for 2D Active Shape Recognition using Fourier Descriptors and Mutual Information
Natasha Govender, Jonathan Warrell, Philip H.S. Torr, Fred Nicolls
Advances in Computer Science
[PDF]

Learning discriminative space-time action parts from weakly labelled videos
Michael Sapienza, Fabio Cuzzolin, Philip H.S. Torr
International Journal of Computer Vision
[PDF]

ImageSpirit:Verbal Guided Image Parsing
Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Vibhav Vineet, Paul Sturgess, Nigel Crook, Niloy J. Mitra, Philip H.S. Torr
ACM Transactions on Graphics
[PDF]

Higher Order Models and Inference Approaches in Computer Vision
Vibhav Vineet, Philipp Kraehenbuehl, Lubor Ladicky, Pushmeet Kohli, Philip H.S. Torr
Full day tutorial at ECCV 2014 - European Conference on Computer Vision
[PDF]

Global Contrast based Salient Region Detection
Ming-Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Philip H.S. Torr, Shi-Min Hu
IEEE TPAMI
[PDF]

Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces
Vibhav Vineet, Jonathan Warrell, Philip H.S. Torr
International Journal of Computer Vision (IJCV)
[PDF]

Exploiting projective geometry for view-invariant monocular human motion analysis in man-made environments
Gregory Rogez, Carlos Orrite, J.J. Guerrero, Philip H.S. Torr
Computer Vision and Image Understanding
[PDF]

Distributed Non-Convex ADMM-inference in Large-scale Random Fields
Ondrej Miksik, Vibhav Vineet, Patrick Perez, Philip H.S. Torr
British Machine Vision Conference (BMVC)
[PDF]

Dense Semantic Image Segmentation with Objects and Attributes
Shuai Zheng, Ming-Ming Cheng, Jonathan Warrell, Paul Sturgess, Vibhav Vineet, Carsten Rother, Philip H.S. Torr
In Proceedings of Computer Vision and Pattern Recognition (CVPR)
[PDF]

Bilateral Functions for Global Motion Modeling
Wen-Yan Lin, Ming-Ming Cheng, Jiangbo Lu, Hongsheng Yang, Minh N. Do, Philip H.S. Torr
ECCV - European Conference on Computer Vision
[PDF]

BING:Binarized Normed Gradients for Objectness Estimation at 300fp
Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, Philip H.S. Torr
IEEE International Conference on Computer Vision and Pattern Recognition (IEEE CVPR)
[PDF]

Urban 3D Semantic Modelling Using Stereo Vision
Sunando Sengupta, Eric Greveson, A. Shahrokni, Philip H.S. Torr
In Proceedings of IEEE International Conference on Robotics and Automation (ICRA)
[PDF]

SalientShape:Group Saliency in Image Collections
Ming-Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Shi-Min Hu
The Visual Computer
[PDF]

Probabilistic Object and Viewpoint Models for Active Object Recognition
Natasha Govender, Jonathan Warrell, Philip H.S. Torr, Test Person, Fred Nicolls
In Proceedings of Africon
[PDF]

PoseField:An Efficient Mean-field based Method for Joint Estimation of Human Pose, Segmentation, and Depth
Vibhav Vineet, Glenn Sheasby, Jonathan Warrell, Philip H.S. Torr
In Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)
[PDF]

Non-Parametric Correspondence Fitting
Wen-Yan Lin, Ming-Ming Cheng, Shuai Zheng, Jiangbo Lu, Nigel Crook
IEEE International Conference on Computer Vision (IEEE ICCV)
[PDF]

Mesh Based Semantic Modelling for Indoor and Outdoor Scenes
Julien Valentin, Sunando Sengupta, Jonathan Warrell, A. Shahrokni, Philip H.S. Torr
In Proceedings of Computer Vision and Pattern Recognition (CVPR)
[PDF]

Learning pullback HMM distances
Fabio Cuzzolin, Michael Sapienza
IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

Inference Methods for CRFs with Co-occurrence Statistics
Lubor Ladicky, Chris Russell, Pushmeet Kohli, Philip H.S. Torr
International Journal of Computer Vision
[PDF]

Human Pose Estimation using a Joint Pixel-wise and Part-wise Formulation
Lubor Ladicky, Philip H.S. Torr, Andrew Zisserman
In Proceedings of Computer Vision and Pattern Recognition (CVPR)
[PDF]

Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation
Vibhav Vineet, Carsten Rother, Philip H.S. Torr
Neural Information Processing System (NIPS)
[PDF]

Efficient Salient Region Detection with Soft Image Abstraction
Ming-Ming Cheng, Jonathan Warrell, Wen-Yan Lin, Shuai Zheng, Vibhav Vineet, Nigel Crook
IEEE International Conference on Computer Vision (IEEE ICCV)
[PDF]

Beyond Controllers - Human Segmentation, Pose, and Depth Estimation as Game Input Mechanisms
Glenn Sheasby
Oxford Brookes University, March 2013
[PDF]

Approximate Structured Output Learning for Constrained Local Models with Application to Real-time Facial Feature Detection and Tracking on Low-power Devices
Shuai Zheng, Paul Sturgess, Philip H.S. Torr
In Proceedings of IEEE Conference on Automatic Face and Gesture Recognition (FG)
[PDF]

Alternating Decision Forests
Samuel Schulter, Paul Wohlhart, Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof
In Proceedings of Computer Vision and Pattern Recognition (CVPR)
[PDF]

Active Object Recognition using Vocabulary Trees
Natasha Govender, Jonathan Claassens, Philip H.S. Torr, Jonathan Warrell
In Proceedings of Workshop on Robot Vision, Florida
[PDF]

Taxonomic Multi-class Prediction and Person Layout using Efficient Structured Ranking
A. Mittal, Matthew B. Blaschko, Andrew Zisserman, Philip H.S. Torr
In Proceedings of European Conference on Computer Vision
[PDF]

Simultaneous Human Segmentation, Depth and Pose Estimation via Dual Decomposition
Glenn Sheasby, Jonathan Warrell, Yuhang Zhang, Nigel Crook, Philip H.S. Torr
In Proceedings of the workshop of British Machine Vision Conference (BMVC)
[PDF]

Scalable Cascade Inference for Semantic Image Segmentation
Paul Sturgess, Lubor Ladicky, Nigel Crook, Philip H.S. Torr
In Proceedings of British Machine Vision Conference (BMVC)
[PDF]

Online Structured Learning for Real-Time Computer Vision Gaming Applications
Sam Hare
Department of Computing, Oxford Brookes University
[PDF]

Learning discriminative space-time actions from weakly labelled videos
Michael Sapienza, Fabio Cuzzolin, Philip H.S. Torr
In the Proceedings British Machine Vision Conference (BMVC)
[PDF]

Latent SVMs for Human Detection with a Locally Affine Deformation Field
Lubor Ladicky, Philip H.S. Torr, Andrew Zisserman
In Proceedings of British Machine Vision Conference (BMVC)
[PDF]

Improved Initialisation and Gaussian Mixture Pairwise Terms for Dense Random Fields with Mean-field Inference
Vibhav Vineet, Jonathan Warrell, Paul Sturgess, Philip H.S. Torr
In the Proceedings British Machine Vision Conference (BMVC)
[PDF]

Human Layout Estimation using Structured Output Learning
A. Mittal
Department of Engineering Science, University of Oxford, Co-Supervised with Professor Zisserman, University of Oxford
[PDF]

Filter-based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces
Vibhav Vineet, Jonathan Warrell, Philip H.S. Torr
In the Proceedings of the European Conference on Computer Vision
[PDF]

Fast Human Pose Detection Using Randomized Hierarchical Cascades of Rejectors
Gregory Rogez, Jon Rihan, Carlos Orrite, Philip H.S. Torr
Proceedings International Journal of Computer Vision
[PDF]

Efficient Online Structured Output Learning for Keypoint-Based Object Tracking
Sam Hare, Amir Saffari, Philip H.S. Torr
In the Proceedings IEEE Conference of Computer Vision and Pattern Recognition (CVPR)
[PDF]

Efficient Discriminative Learning of Parametric Nearest Neighbor Classifiers
Ziming Zhang, Paul Sturgess, Sunando Sengupta, Nigel Crook, Philip H.S. Torr
In the Proceedings IEEE Conference of Computer Vision and Pattern Recognition (CVPR)
[PDF]

Automatic Dense Visual Semantic Mapping from Street-Level Imagery
Sunando Sengupta, Paul Sturgess, Lubor Ladicky, Philip H.S. Torr
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
[PDF]

A robust stereo prior for human segmentation
Glenn Sheasby, Julien Valentin, Nigel Crook, Philip H.S. Torr
In Proceedings of Asian Conference on Computer Vision (ACCV)
[PDF]

A Tiered Move-making Algorithm for General Pairwise MRF.s
Vibhav Vineet, Jonathan Warrell, Philip H.S. Torr, Jonathan Warrell
In the Proceedings IEEE Conference of Computer Vision and Pattern Recognition (CVPR)
[PDF]

The Light-Path Less Traveled
S. Ramalingham, S. Bouaziz, P. Sturm, Philip H.S. Torr
Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Struck:Structured Output Tracking with Kernels
Philip H.S. Torr, Amir Saffari, Sam Hare, Sam Hare
IEEE ICCV, 2011
[PDF]

Proposal Generation for Object Detection using Cascaded Ranking SVMs
Ziming Zhang, Jonathan Warrell, Philip H.S. Torr
Proceedings IEEE Conference on Computer Vision and Pattern Recognition
[PDF]

Locally Multiple-Instance Learning with Structured Bag Models
Jonathan Warrell, Philip H.S. Torr
Proceedings Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)
[PDF]

Locally Linear Support Vector Machines
Lubor Ladicky, Philip H.S. Torr
Proceedings International Conference of Machine Learning (ICML)
[PDF]

Learning Anchor Planes for Classification
Ziming Zhang, Lubor Ladicky, Philip H.S. Torr, Amir Saffari
NIPS
[PDF]

Joint Optimisation for Object Class Segmentation and Dense Stereo Reconstruction
Lubor Ladicky, Paul Sturgess, Chris Russell, Sunando Sengupta, Yalin Bastanlar, William Clocksin, Philip H.S. Torr, Lubor Ladicky, Paul Sturgess, Chris Russell, Sunando Sengupta, Yalin Bastanlar, William Clocksin, Philip H.S. Torr
International Journal of Computer Vision, BMVC special award issue
[PDF]

Inference Methods for CRFs with Co-occurence Statistics
Lubor Ladicky, Chris Russell, Pushmeet Kohli, Philip H.S. Torr
International Journal of Computer Vision, ECCV special award issue
[PDF]

Improving Classifiers with Unlabeled Weakly-Related Videos
Christian Leistner, Marting Godec, Samuel Schulter, Amir Saffari, Manuel Werlberger, Horst Bischof
Proceedings CVPR
[PDF]

Improved Moves for Truncated Convex Models
Philip H.S. Torr, M Pawan Kumar, M Pawan Kumar, Olga Veksler, Philip H.S. Torr
Journal of Machine Learning Research
[PDF]

Human Instance Segmentation from Video using Detector-based Conditional Random Fields
Vibhav Vineet, Jonathan Warrell, Philip H.S. Torr
Proceedings British Machine Vision Conference
[PDF]

Higher-Order Inference for Vision Problems
Chris Russell
Oxford Brookes University, July 2011
[PDF]

Hands-On Pattern Recognition Challenges in Machine Learning, Volume 1
Isabelle Guyon, Gavin Cawley, Gideon Dror, Amir Saffari
Microtome Publishing,Brookline, Massachusetts, 2011
[PDF]

Hand detection using multiple proposals
A. Mittal, Andrew Zisserman, Philip H.S. Torr
Proceedings British Machine Vision Conference
[PDF]

Global Structured Models towards Scene Understanding
Lubor Ladicky
Oxford Brookes University, April 2011
[PDF]

Computer Vision Based Interfacess for Computer Games
Jon Rihan
PhD Thesis
[PDF]

What,Where & How Many? Combining Object Detectors and CRFs
Lubor Ladicky, Paul Sturgess, Karteek Alahari, Chris Russell, Philip H.S. Torr
Proceedings of the Eleventh European Conference on Computer Vision
[PDF]

The Quantification of Volumetric Asymmetry by Dynamic Surface Topography
Tom Shannon
International Research Society of Spinal Deformities Conference, Montreal, 1st-3rd July
[PDF]

StyP-Boost:A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers
Jonathan Warrell, Simon Prince, Philip H.S. Torr
Proceedings British Machine Vision Conference
[PDF]

OBJCUT:Efficient Segmentation Using Top-Down and Bottom-Up Cues
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
Proceedings IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

Measurement of the Positional Variability of Surface Anatomical Landmarks over Time
Tom Shannon
International Research Society of Spinal Deformities Conference, Montreal, 1st-3rd July
[PDF]

Graph Cut based Inference with Co-occurrence Statistics
Pushmeet Kohli, Chris Russell, Lubor Ladicky, Philip H.S. Torr
Proceedings of the Eleventh European Conference on Computer Vision
[PDF]

Exact and Approximate Inference in Associative Hierarchical Random Fields using Graph-Cuts
Chris Russell, Lubor Ladicky, Pushmeet Kohli, Philip H.S. Torr
The 26th Conference on Uncertainty in Artificial Intelligence
[PDF]

Efficient inference and learning for computer vision labelling problems
Karteek Alahari
PhD Thesis
[PDF]

Efficient Piecewise Learning for Conditional Random Fields
Karteek Alahari, Chris Russell, Philip H.S. Torr
Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Dynamic Surface Topography and its application to the evaluation of adolescent idiopathic scoliosis
Tom Shannon
PhD Thesis
[PDF]

Dynamic Hybrid Algorithms for MAP Inference in Discrete MRFs
Karteek Alahari, Pushmeet Kohli, Philip H.S. Torr
In Proceedings IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

Discrete minimum ratio curves and surfaces
Fred Nicholls, Philip H.S. Torr
Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

US Patent Application 20090009513 - METHOD AND SYSTEM FOR GENERATING A 3D MODEL
Anton van den Hengel, Anthony Dick, Thorsten Thormählen, Ben Ward, Philip H.S. Torr

[PDF]

Three alternative combinatorial formulations of the theory of evidence
Fabio Cuzzolin
Special Issue of PRICAI '08 Selected Papers, Intelligent Decision Analysis journal
[PDF]

The intersection probability and its properties
Fabio Cuzzolin
European Conference on Symbolic and Quantitative Reasoning under Uncertainty
[PDF]

Shared Gaussian Process Latent Variable Models
Carl Henrik Ek
PhD Thesis
[PDF]

Robust Higher Order Potentials for Enforcing Label Consistency
Pushmeet Kohli, Lubor Ladicky, Philip H.S. Torr, Pushmeet Kohli, Lubor Ladicky, Philip H.S. Torr
In Proceedings of the International Journal of Computer Vision
[PDF]

Global Stereo Reconstruction under Second Order Smoothness Priors
Oliver Woodford, Philip H.S. Torr, I. Reid, A.W. Fitzgibbon, Oliver Woodford, Philip H.S. Torr, I. Reid, A.W. Fitzgibbon
Proceedings IEEE Transactions on Pattern Analysis and Machine Intelligence
[PDF]

Efficient Discriminative Learning of Parts-based Models
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
Proceedings IEEE Twelfth International Conference on Computer Vision
[PDF]

Credal semantics of Bayesian approximations
Fabio Cuzzolin
Proceedings of the International Symposium on Imprecise Probabilities and Their Applications (ISIPTA'09)
[PDF]

Credal semantics of Bayesian approximations in terms of probability intervals
Fabio Cuzzolin
IEEE Transaction on Systems, Man, and Cybernetics
[PDF]

Complexes of outer consonant approximations
Fabio Cuzzolin
European Conference on Symbolic and Quantitative Reasoning under Uncertainty
[PDF]

Combining Appearance and Structure from Motion Features for Road Scene Understanding
Paul Sturgess, Karteek Alahari, Lubor Ladicky, Philip H.S. Torr
Proceedings British Machine Vision Conference,
[PDF]

Associative Hierarchical CRFs for Object Class Image Segmentation
Lubor Ladicky, Chris Russell, Pushmeet Kohli, Philip H.S. Torr
Proceedings IEEE Twelfth International Conference on Computer Vision
[PDF]

An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs
V. Kolmogorov, M Pawan Kumar, Philip H.S. Torr, M Pawan Kumar, V. Kolmogorov, Philip H.S. Torr
In Journal of Machine Learning Research (JMLR)
[PDF]

Simultaneous Segmentation and Pose Estimation of Humans using Dynamic Graph Cuts
Pushmeet Kohli, Jon Rihan, Matthieu Bray, Philip H.S. Torr
In International Journal of Computer Vision
[PDF]

Semantics of the relative belief of singletons
Fabio Cuzzolin
In 'Interval / Probabilistic Uncertainty and Non-classical Logics', Advances in Soft Computing
[PDF]

Reduce, Reuse & Recycle:Efficiently Solving Multi-Label MRFs
Karteek Alahari, Pushmeet Kohli, Philip H.S. Torr
In Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Reconstructing Relief Surfaces
George Vogiatzis, Philip H.S. Torr, S.M. Seitz, R. Cipolla
In Image and Vision Computing
[PDF]

Randomized Trees for Human Pose Detection
Gregory Rogez, Jon Rihan, Srikumar Ramalingam, Carlos Orrite, Philip H.S. Torr
In Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Pose Estimation and Tracking using Multivariate Regression
Arasanathan Thayanantha, R. Navaratnam, Bjorn Stenger
In Pattern Recognition Letters
[PDF]

P3 & Beyond:Move Making Algorithms for Solving Higher Order Functions
Pushmeet Kohli, M Pawan Kumar, Philip H.S. Torr
In IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

On the credal structure of consistent probabilities
Fabio Cuzzolin
In 'Logics in Artificial Intelligence', Lecture Notes in Computer Science
[PDF]

On Partial Optimality in Multi-label MRFs
Pushmeet Kohli, A. Shekhovtsov, V. Kolmogorov, Carsten Rother, Philip H.S. Torr
In Proceedings International Conference of Machine Learning (ICML)
[PDF]

Minimizing Dynamic and Higher Order Energy Functions using Graph Cuts
Pushmeet Kohli
PhD Thesis
[PDF]

Minimal Solutions for Generic Imaging Models
Srikumar Ramalingam, P. Sturm
In Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Measuring Uncertainty in Graph Cut Solutions
Philip H.S. Torr, Pushmeet Kohli
In Journal of Computer Vision and Image Understanding, special issue Discrete Optimization in Computer Vision
[PDF]

Learning pullback metrics for linear models
Fabio Cuzzolin
In Proceedings of the first workshop on Machine Learning for Vision-based Motion Analysis - ECCV'08
[PDF]

Learning Layered Motion Segmentations of Video
Andrew Zisserman, Philip H.S. Torr, M Pawan Kumar
In International Journal of Computer Vision
[PDF]

Layered Motion Segmentations of Video
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
In International Journal of Computer Vision, 76
[PDF]

LP-relaxation of binarized energy minimization
V. Hlavac, Pushmeet Kohli, V. Kolmogorov, A. Shekhovtsov, Carsten Rother, Philip H.S. Torr
Research Report CTU--CMP--2007—27, Czech Technical University, update 2008
[PDF]

From Visual Query to Visual Portrayal
A. Shahrokni, C. Mei, Philip H.S. Torr, I. Reid
In Proceedings of the British Machine Vision Conference
[PDF]

Exact Inference in Multi-label CRFs with Higher Order Cliques
Srikumar Ramalingam, Pushmeet Kohli, Karteek Alahari, Philip H.S. Torr
In Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Efficiently Solving Convex Relaxations for MAP Estimation
M Pawan Kumar, Philip H.S. Torr
In Proceedings International Conference of Machine Learning (ICML)
[PDF]

Dual properties of the relative belief of singletons
Fabio Cuzzolin
In Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI'08)
[PDF]

Development of an Apparatus to Evaluate Adolescent Idiopathic Scoliosis by Dynamic Surface Topography
Tom Shannon
In Proceedings of the International Research Society of Spinal Deformities Meeting
[PDF]

Computer Vision - ECCV 2008
David A. Forsyth, Philip H.S. Torr, Andrew Zisserman
10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008
[PDF]

Combinatorial and Convex Optimization for Probabilistic Models in Computer Vision
M Pawan Kumar
PhD Thesis
[PDF]

Coherent Laplacian protrusion segmentation
Fabio Cuzzolin, Diana Mateus, David Knossow, Edmond Boyer, R. Horaud
Proceedings of CVPR'08
[PDF]

Boolean and matroidal independence in uncertainty theory
Fabio Cuzzolin
In Proceedings of the 10th International Symposium on Mathematics and Artificial Intelligence ISAIM'08
[PDF]

Body Language Based Individual Identification in Video Using Gait and Actions
Yogarajah Pratheepan, Philip H.S. Torr, Joan Condell, M. Prasad
In Proceedings of the International Machine Vision and Image Processing Conference
[PDF]

Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration
Diana Mateus, R. Horaud, David Knossow, Fabio Cuzzolin, Edmond Boyer
Proceedings of CVPR'08
[PDF]

An interpretation of consistent belief functions in terms of simplicial complexes
Fabio Cuzzolin
In Proceedings of the 10th International Symposium on Mathematics and Artificial Intelligence ISAIM'08,
[PDF]

Ambiguity Modeling in Latent Spaces
N. Lawrence, Philip H.S. Torr, Gregory Rogez, Jon Rihan, Carl Henrik Ek
In Machine Learning for Multimodal Interaction
[PDF]

Alternative formulations of the theory of evidence based on basic plausibility and commonality assignments
Fabio Cuzzolin
In Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI'08)
[PDF]

A lattice-theoretic interpretation of independence on frames
Fabio Cuzzolin
In 'Interval / Probabilistic Uncertainty and Non-classical Logics', Advances in Soft Computing
[PDF]

A geometric approach to the theory of evidence
Fabio Cuzzolin
IEEE Transactions on Systems, Man, and Cybernetics
[PDF]

VideoTrace:Rapid interactive scene modelling from video
Anton van den Hengel, Anthony Dick, Thorsten Thormählen, Ben Ward, Philip H.S. Torr
In ACM Transactions on Graphics (SIGGRAPH special issue)
[PDF]

Using the P^n Potts model with learning methods to segment live cell images
Chris Russell, Christophe Restif, D. Metaxas, Philip H.S. Torr
In IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis
[PDF]

Revisiting the Evaluation of Segmentation Results:Introducing Confidence Maps
Christophe Restif
International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI
[PDF]

P3 & Beyond:Solving Energies with Higher Order Cliques
Pushmeet Kohli, M Pawan Kumar, Philip H.S. Torr
In Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

On New View Synthesis Using Multiview Stereo
Oliver Woodford, I. Reid, Philip H.S. Torr, A.W. Fitzgibbon
In Proceedings British Machine Vision Conference
[PDF]

Multi-view stereo via Volumetric Graph-cuts and Occlusion Robust Photo Consistency
George Vogiatzis, C.H. Esteban, Philip H.S. Torr, R. Cipolla
In IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

Graph Cuts and their Use in Computer Vision
Philip H.S. Torr
Invited tutorial at International Computer Vision Summer School 2007, Detection, Recognition and Segmentation in Context
[PDF]

Gaussian Process Latent Variable Models for Human Pose Estimation
Carl Henrik Ek, Philip H.S. Torr, N. Lawrence
In 4th Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms
[PDF]

Estimating 3D hand pose using hierarchical multi-label classification
Bjorn Stenger, Arasanathan Thayanantha, Philip H.S. Torr, R. Cipolla
In Image and Vision Computing
[PDF]

Efficient Dense Stereo with Occlusions for New View Synthesis by Four State Dynamic Programming
Antonio Criminisi, Jamie Shotton, A. Blake, Carsten Rother, Philip H.S. Torr
In International Journal of Computer Vision
[PDF]

Dynamic Graph Cuts for Efficient Inference in Markov Random Fields
Pushmeet Kohli, Philip H.S. Torr
In IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

Discrete Optimization in Computer Vision
N. Komodakis, Philip H.S. Torr, V. Kolmogorov, Y. Boykov
Invited tutorial at Iternational Conference on Computer Vision, ICCV
[PDF]

An Invariant Large Margin Nearest Neighbour Classifier
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
In IEEE Eleventh International Conference on Computer Vision
[PDF]

An Analysis of Convex Relaxations for MAP Estimation
M Pawan Kumar, V. Kolmogorov, Philip H.S. Torr
In Neural Information Processing Conference, NIPS
[PDF]

Using Strong Shape Priors for Stereo
Yunda Sun, Pushmeet Kohli, Matthieu Bray, Philip H.S. Torr
In ICVGIP (2006)
[PDF]

Towards Safer, Faster Prenatal Genetic Tests:Novel Unsupervised, Automatic and Robust Methods of Segmentation of Nuclei and Probes
Christophe Restif
In the Proceedings of the Ninth European Conference on Computer Vision 2006
[PDF]

Solving Markov Random Fields Using Second Order Cone Programming
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
In Proceedings IEEE Conference of Computer Vision and Pattern Recognition
[PDF]

Regression-Based Human Motion Capture From Voxel Data
Yunda Sun, Matthieu Bray, Arasanathan Thayanantha, B. Yuanand, Philip H.S. Torr
In Proceedings British Machine Vision Conference
[PDF]

Rapid Interactive Modelling from Video with Graph Cuts
Anton van den Hengel, Anthony Dick, Thorsten Thormählen, Ben Ward, Philip H.S. Torr
In Proceedings Eurographics
[PDF]

PoseCut:Simultaneous Segmentation and 3D Pose Estimation of Humans using Dynamic Graph-Cuts
Matthieu Bray, Pushmeet Kohli, Philip H.S. Torr
In the Proceedings of the Ninth European Conference on Computer Vision 2006
[PDF]

ObjCut for Face Detection
Jon Rihan, Pushmeet Kohli, Philip H.S. Torr
In ICVGIP (2006)
[PDF]

Multivariate Relevance Vector Machines for Tracking
Arasanathan Thayanantha, R. Navaratnam, Bjorn Stenger, Philip H.S. Torr, R. Cipolla
In the Proceedings of the Ninth European Conference on Computer Vision 2006
[PDF]

Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
Bjorn Stenger, Arasanathan Thayanantha, Philip H.S. Torr, R. Cipolla
In IEEE Trans Pattern Analysis and Machine Intelligence
[PDF]

Measuring Uncertainty in Graph Cut Solutions - Efficiently Computing Min-marginal Energies using Dynamic Graph Cuts
Pushmeet Kohli, Philip H.S. Torr
In the Proceedings of the Ninth European Conference on Computer Vision 2006
[PDF]

Maximization of mutual information for offline Thai handwriting recognition
N. Nopsuwanchai, A. Biem, William Clocksin
In IEEE Transactions on Pattern Analysis and Machine Intelligence
[PDF]

Learning Class-specific Edges for Object Detection and Segmentation
M. Prasad, Andrew Zisserman, A.W. Fitzgibbon, M Pawan Kumar, Philip H.S. Torr
In ICVGIP (2006)
[PDF]

International Workshop on the Representation and Use of Prior Knowledge in Vision
R. Horaud, C. Schnorr, Philip H.S. Torr, J. Tsostsos
In International Workshop on the Representation and Use of Prior Knowledge in Vision (WRUPKV)
[PDF]

Hierarchical model fitting to 2D and 3D data
Anton van den Hengel, Anthony Dick, Thorsten Thormählen, Ben Ward, Philip H.S. Torr
In Proceedings of the Third International Conference on Computer Graphics, Imaging and Visualisation
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Fitting multiple models to multiple images with minimal user interaction
Anton van den Hengel, Anthony Dick, Thorsten Thormählen, Ben Ward, Philip H.S. Torr
In International Workshop on the Representation and Use of Prior Knowledge in Vision (WRUPKV)
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Fields of Experts for Image-based Rendering
Oliver Woodford, I. Reid, Philip H.S. Torr, A.W. Fitzgibbon
In Proceedings British Machine Vision Conference
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Fast Memory-Efficient Generalized Belief Propagation
M Pawan Kumar, Philip H.S. Torr
In the Proceedings of the Ninth European Conference on Computer Vision 2006
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Building Models of Regular Scenes from Structure and Motion
Anton van den Hengel, Anthony Dick, Thorsten Thormählen, Ben Ward, Philip H.S. Torr
In Proceedings British Machine Vision Conference
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An Object Category Specific MRF for Segmentation
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
In Toward Category-Level Object Recognition
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Template-based hand detection and tracking
R. Cipolla, Bjorn Stenger, Arasanathan Thayanantha, Philip H.S. Torr
In Advanced Studies in Biometrics
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Rank Mini Symposium on Machine Understanding of People and their Responses
J. Mollon, FRS, Philip H.S. Torr

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OBJCUT
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
In Proceedings of IEEE Conference of Computer Vision and Pattern Recognition, 2005
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Multi-view stereo via Volumetric Graph-cuts
George Vogiatzis, Philip H.S. Torr, R. Cipolla
In Proceedings of IEEE Conference of Computer Vision and Pattern Recognition
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Markov Random Fields for Computer Vision and Graphics
Philip H.S. Torr
Invited tutorial at Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI
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Hierarchical Part-Based Human Body Pose Estimation
R. Navaratnam, Philip H.S. Torr, R. Cipolla
In Proceedings of British Machine Vision Conference, 2005. (oral).
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Efficiently Solving Dynamic Markov Random Fields Using Graph Cuts
Pushmeet Kohli, Philip H.S. Torr
In Proceedings of IEEE Tenth International Conference on Computer Vision 2005
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British Machine Vision Conference
William Clocksin, A.W. Fitzgibbon, Philip H.S. Torr
In ISBN 1-901725-29-4
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An Exploration of the SIFT operator
Jon Rihan, Philip H.S. Torr
Dissertation for MSc Computing degree
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Modelling and Interpretation of Architecture from Several Images
Anthony Dick, Philip H.S. Torr, R. Cipolla
In International Journal of Computer Vision
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Likelihood Models for Template Matching
Arasanathan Thayanantha, R. Navaratnam, Philip H.S. Torr, R. Cipolla
In Proceedings British Machine Vision Conference
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Learning Layered Pictorial Structures from Video
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
In proceedings of The Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP)
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Interactive Image Segmentation Using an Adaptive GMMRF Model
A. Blake, Carsten Rother, M. Brown, Patrick Perez, Philip H.S. Torr
In The Eighth European Conference on Computer Vision
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Hand Pose Estimation Using Hierarchical Detection
Bjorn Stenger, Arasanathan Thayanantha, Philip H.S. Torr, R. Cipolla
In International Workshop on Human-Computer Interaction
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Geometric Structure Computations from Conics
M Pawan Kumar, C.V. Jawahar, P.J. Narayanan
In Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP)
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Efficient Face Detection by a Cascaded Reduced Support Vector Expansion
S. Romdhani, Philip H.S. Torr, B. Schölkopf, A. Blake
In Proceedings of the Royal Society Series A
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Discrete Optimization Methods
Y. Boykov, Philip H.S. Torr, R. Zabih
Invited tutorial at Eighth European Conference on Computer Vision
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Detecting Articulated Objects Using Pictorial Structures
M Pawan Kumar, Philip H.S. Torr, Andrew Zisserman
Proceedings British Machine VisionConference
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Comparison of segmentation methods for cytometric assay
Christophe Restif, William Clocksin
In Proceedings of the Medical Image Understanding and Analysis 2004
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Bayesian Methods in Computer Vision and Graphics
Philip H.S. Torr
Keynote Talk for Prasa 15th Annual Symposium of the Pattern Recognition Association of South Africa
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Tracking Articulated Hand Motion using a Kinematic Prior
Arasanathan Thayanantha, Bjorn Stenger, Philip H.S. Torr, R. Cipolla
In Proceedings British Machine Vision Conference
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Solving Markov Random Fields using Semi Definite Programming
Philip H.S. Torr
In Ninth International Workshop on Artificial Intelligence and Statistics
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Shape Context and Chamfer Matching in Cluttered Scenes
Arasanathan Thayanantha, Bjorn Stenger, Philip H.S. Torr
In Conference of Computer Vision and Pattern Recognition
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Modelling Articulated Hand Motion
R. Cipolla, Bjorn Stenger, Arasanathan Thayanantha, Philip H.S. Torr
R. Cipolla Invited Key Note Speech, for The Mathematics of Surfaces X
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Invariant Fitting of Two View Geometry or 'In Defiance of the eight point algorithm'
Philip H.S. Torr, A.W. Fitzgibbon, Philip H.S. Torr, A.W. Fitzgibbon
In Proceedings British Machine Vision Conference
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IMPSAC:A synthesis of importance sampling and random sample consensus
Philip H.S. Torr, C. Davidson
In IEEE Trans Pattern Analysis and Machine Intelligence
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Gaze Manipulation for One-to-one Teleconferencing
Jamie Shotton, Antonio Criminisi, A. Blake, Philip H.S. Torr
In IEEE Ninth International Conference on Computer Vision
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First International Workshop on use of Higher Level Knowledge in Vision
F. Dellaert, Philip H.S. Torr, S. B. Kang, R. Cipolla
ISBN 0-7695-2049-9
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Efficient Algorithms for Matching. Short Course
D. Huttenlocher, Philip H.S. Torr
Invited tutorial at Ninth International Conference on Computer Vision
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Dense Stereo using Pivoted Dynamic Programming
Philip H.S. Torr, Antonio Criminisi, Philip H.S. Torr, Antonio Criminisi
Vision
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Bayesian Tracking using Tree-Based Density Estimation
Bjorn Stenger, Arasanathan Thayanantha, Philip H.S. Torr, R. Cipolla
In IEEE Ninth International Conference on Computer Vision
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Bayesian Stochastic Mesh Optimization for 3D Reconstruction
George Vogiatzis, Philip H.S. Torr, R. Cipolla
In Proceedings British Machine Vision Conference
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Bayesian Methods in Graphics
Philip H.S. Torr
Keynote Talk for GraphiCon 13th Int. Conf. of Computer Graphics and Vision
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