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ORCIDPhilip H. S. Torr
Philip Hilaire Sean Torr
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- affiliation: University of Oxford
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2020 – today
- 2023
[j73]Hao Tang
, Ling Shao, Philip H. S. Torr, Nicu Sebe:
Local and Global GANs With Semantic-Aware Upsampling for Image Generation. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 768-784 (2023)- [j72]Thomas Tanay, Aivar Sootla, Matteo Maggioni, Puneet K. Dokania, Philip H. S. Torr, Ales Leonardis, Gregory G. Slabaugh:
Diagnosing and Preventing Instabilities in Recurrent Video Processing. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1594-1605 (2023) - 2022
- [j71]Jiyang Qi, Yan Gao, Yao Hu, Xinggang Wang, Xiaoyu Liu, Xiang Bai, Serge J. Belongie, Alan L. Yuille, Philip H. S. Torr, Song Bai:
Occluded Video Instance Segmentation: A Benchmark. Int. J. Comput. Vis. 130(8): 2022-2039 (2022) - [j70]Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia:
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 969-984 (2022) - [c289]Motasem Alfarra, Juan C. Pérez, Ali K. Thabet, Adel Bibi, Philip H. S. Torr, Bernard Ghanem:
Combating Adversaries with Anti-adversaries. AAAI 2022: 5992-6000 - [c288]Motasem Alfarra, Adel Bibi, Naeemullah Khan, Philip H. S. Torr, Bernard Ghanem:
DeformRS: Certifying Input Deformations with Randomized Smoothing. AAAI 2022: 6001-6009 - [c287]Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood:
Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS 2022: 8392-8412 - [c286]Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip H. S. Torr, Guoying Zhao:
PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer. CVPR 2022: 4176-4186 - [c285]Kejie Li, Yansong Tang, Victor Adrian Prisacariu, Philip H. S. Torr:
BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion. CVPR 2022: 6156-6165 - [c284]Guangrun Wang, Yansong Tang, Liang Lin, Philip H. S. Torr:
Semantic-Aware Auto-Encoders for Self-supervised Representation Learning. CVPR 2022: 9654-9665 - [c283]Jieneng Chen, Shuyang Sun, Ju He, Philip H. S. Torr, Alan L. Yuille, Song Bai:
TransMix: Attend to Mix for Vision Transformers. CVPR 2022: 12125-12134 - [c282]Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip H. S. Torr, Song Bai, Vincent Y. F. Tan:
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning. CVPR 2022: 16701-16710 - [c281]Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip H. S. Torr:
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation. CVPR 2022: 18134-18144 - [c280]Donglai Wei, Siddhant Kharbanda, Sarthak Arora, Roshan Roy, Nishant Jain, Akash Palrecha, Tanav Shah, Shray Mathur, Ritik Mathur, Abhijay Kemkar, Anirudh Srinivasan Chakravarthy, Zudi Lin, Won-Dong Jang, Yansong Tang, Song Bai, James Tompkin, Philip H. S. Torr, Hanspeter Pfister:
YouMVOS: An Actor-centric Multi-shot Video Object Segmentation Dataset. CVPR 2022: 21012-21021 - [c279]Motasem Alfarra, Juan C. Pérez, Anna Frühstück, Philip H. S. Torr, Peter Wonka, Bernard Ghanem:
On the Robustness of Quality Measures for GANs. ECCV (17) 2022: 18-33 - [c278]Chuhui Xue, Wenqing Zhang, Yu Hao, Shijian Lu, Philip H. S. Torr, Song Bai:
Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detection and Spotting. ECCV (28) 2022: 284-302 - [c277]Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr:
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness. ECCV (29) 2022: 308-325 - [c276]Francesco Pinto, Philip H. S. Torr, Puneet K. Dokania:
An Impartial Take to the CNN vs Transformer Robustness Contest. ECCV (13) 2022: 466-480 - [c275]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, Siddharth Narayanaswamy:
Learning Multimodal VAEs through Mutual Supervision. ICLR 2022 - [c274]A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Gunes Baydin:
KL Guided Domain Adaptation. ICLR 2022 - [c273]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, Siddharth Narayanaswamy, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. ICLR 2022 - [c272]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. ICML 2022: 20026-20040 - [c271]Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster:
Communicating via Markov Decision Processes. ICML 2022: 20314-20328 - [c270]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Zero-Shot Logit Adjustment. IJCAI 2022: 813-819 - [c269]Jiaguo Yu, Yuming Shen, Menghan Wang, Haofeng Zhang, Philip H. S. Torr:
Learning to Hash Naturally Sorts. IJCAI 2022: 1587-1593 - [c268]Ziyi Shen, Qianye Yang, Yuming Shen, Francesco Giganti, Vasilis Stavrinides, Richard E. Fan, Caroline M. Moore, Mirabela Rusu, Geoffrey A. Sonn, Philip H. S. Torr, Dean C. Barratt, Yipeng Hu:
Collaborative Quantization Embeddings for Intra-subject Prostate MR Image Registration. MICCAI (6) 2022: 237-247 - [c267]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Clustering Generative Adversarial Networks for Story Visualization. ACM Multimedia 2022: 769-778 - [c266]Menghan Wang, Yuchen Guo, Zhenqi Zhao, Guangzheng Hu, Yuming Shen, Mingming Gong, Philip H. S. Torr:
MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning. SIGIR 2022: 2105-2109 - [c265]Motasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem:
Data dependent randomized smoothing. UAI 2022: 64-74 - [i220]Ming-Ming Cheng, Peng-Tao Jiang, Linghao Han, Liang Wang, Philip H. S. Torr:
Deeply Explain CNN via Hierarchical Decomposition. CoRR abs/2201.09205 (2022) - [i219]Motasem Alfarra, Juan C. Pérez, Anna Frühstück, Philip H. S. Torr, Peter Wonka, Bernard Ghanem:
On the Robustness of Quality Measures for GANs. CoRR abs/2201.13019 (2022) - [i218]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. CoRR abs/2201.13100 (2022) - [i217]Yuming Shen, Jiaguo Yu, Haofeng Zhang, Philip H. S. Torr, Menghan Wang:
Learning to Hash Naturally Sorts. CoRR abs/2201.13322 (2022) - [i216]Pau de Jorge, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip H. S. Torr, Grégory Rogez, Puneet K. Dokania:
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training. CoRR abs/2202.01181 (2022) - [i215]Atilim Günes Baydin, Barak A. Pearlmutter, Don Syme, Frank Wood, Philip H. S. Torr:
Gradients without Backpropagation. CoRR abs/2202.08587 (2022) - [i214]Hao Tang, Ling Shao, Philip H. S. Torr, Nicu Sebe:
Local and Global GANs with Semantic-Aware Upsampling for Image Generation. CoRR abs/2203.00047 (2022) - [i213]Chuhui Xue, Yu Hao, Shijian Lu, Philip H. S. Torr, Song Bai:
Language Matters: A Weakly Supervised Pre-training Approach for Scene Text Detection and Spotting. CoRR abs/2203.03911 (2022) - [i212]A. Tuan Nguyen, Ser Nam Lim, Philip H. S. Torr:
Task-Agnostic Robust Representation Learning. CoRR abs/2203.07596 (2022) - [i211]Kejie Li, Yansong Tang, Victor Adrian Prisacariu, Philip H. S. Torr:
BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion. CoRR abs/2204.01139 (2022) - [i210]Menghan Wang, Yuchen Guo, Zhenqi Zhao, Guangzheng Hu, Yuming Shen, Mingming Gong, Philip H. S. Torr:
MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning. CoRR abs/2204.08326 (2022) - [i209]Feihu Zhang, Vladlen Koltun, Philip H. S. Torr, René Ranftl, Stephan R. Richter:
Unsupervised Contrastive Domain Adaptation for Semantic Segmentation. CoRR abs/2204.08399 (2022) - [i208]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Towards the Semantic Weak Generalization Problem in Generative Zero-Shot Learning: Ante-hoc and Post-hoc. CoRR abs/2204.11280 (2022) - [i207]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Zero-Shot Logit Adjustment. CoRR abs/2204.11822 (2022) - [i206]Guillermo Ortiz-Jiménez, Pau de Jorge, Amartya Sanyal, Adel Bibi, Puneet K. Dokania, Pascal Frossard, Grégory Rogez, Philip H. S. Torr:
Catastrophic overfitting is a bug but also a feature. CoRR abs/2206.08242 (2022) - [i205]Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal:
How robust are pre-trained models to distribution shift? CoRR abs/2206.08871 (2022) - [i204]Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness. CoRR abs/2206.14502 (2022) - [i203]Weiming Hu, Qiang Wang, Li Zhang, Luca Bertinetto, Philip H. S. Torr:
SiamMask: A Framework for Fast Online Object Tracking and Segmentation. CoRR abs/2207.02088 (2022) - [i202]Ziyi Shen, Qianye Yang, Yuming Shen, Francesco Giganti, Vasilis Stavrinides, Richard E. Fan, Caroline M. Moore, Mirabela Rusu, Geoffrey A. Sonn, Philip H. S. Torr, Dean C. Barratt, Yipeng Hu:
Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registration. CoRR abs/2207.06189 (2022) - [i201]Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Sample-dependent Adaptive Temperature Scaling for Improved Calibration. CoRR abs/2207.06211 (2022) - [i200]Xiaogang Xu, Hengshuang Zhao, Philip H. S. Torr:
Universal Adaptive Data Augmentation. CoRR abs/2207.06658 (2022) - [i199]Tim Franzmeyer, João F. Henriques, Jakob N. Foerster, Philip H. S. Torr, Adel Bibi, Christian Schröder de Witt:
Illusionary Attacks on Sequential Decision Makers and Countermeasures. CoRR abs/2207.10170 (2022) - [i198]Francesco Pinto, Philip H. S. Torr, Puneet K. Dokania:
An Impartial Take to the CNN vs Transformer Robustness Contest. CoRR abs/2207.11347 (2022) - [i197]Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr:
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness. CoRR abs/2207.12391 (2022) - [i196]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Memory-Driven Text-to-Image Generation. CoRR abs/2208.07022 (2022) - [i195]Li Zhang, Mohan Chen, Anurag Arnab, Xiangyang Xue, Philip H. S. Torr:
Dynamic Graph Message Passing Networks for Visual Recognition. CoRR abs/2209.09760 (2022) - [i194]Jishnu Mukhoti, Tsung-Yu Lin, Bor-Chun Chen, Ashish Shah, Philip H. S. Torr, Puneet K. Dokania, Ser-Nam Lim:
Raising the Bar on the Evaluation of Out-of-Distribution Detection. CoRR abs/2209.11960 (2022) - [i193]Tim Franzmeyer, Philip H. S. Torr, João F. Henriques:
Learn what matters: cross-domain imitation learning with task-relevant embeddings. CoRR abs/2209.12093 (2022) - [i192]Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip H. S. Torr, Song Bai, Xiaojuan Qi:
Is synthetic data from generative models ready for image recognition? CoRR abs/2210.07574 (2022) - [i191]Nan Xue, Tianfu Wu, Song Bai, Fudong Wang, Gui-Song Xia, Liangpei Zhang, Philip H. S. Torr:
Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning. CoRR abs/2210.12971 (2022) - [i190]Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip H. S. Torr, Liang Lin:
Structure-Preserving 3D Garment Modeling with Neural Sewing Machines. CoRR abs/2211.06701 (2022) - [i189]Hao Tang, Ling Shao, Philip H. S. Torr, Nicu Sebe:
Bipartite Graph Reasoning GANs for Person Pose and Facial Image Synthesis. CoRR abs/2211.06719 (2022) - [i188]Guangrun Wang, Philip H. S. Torr:
Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs. CoRR abs/2211.14794 (2022) - [i187]Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed, Rui Wang, Ashish Shah, Philip H. S. Torr, Ser-Nam Lim:
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning. CoRR abs/2212.04994 (2022) - [i186]Jianhao Yuan, Francesco Pinto, Adam Davies, Aarushi Gupta, Philip H. S. Torr:
Not Just Pretty Pictures: Text-to-Image Generators Enable Interpretable Interventions for Robust Representations. CoRR abs/2212.11237 (2022) - 2021
- [j69]Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip H. S. Torr, Andreas Geiger, Laura Leal-Taixé, Bastian Leibe:
HOTA: A Higher Order Metric for Evaluating Multi-object Tracking. Int. J. Comput. Vis. 129(2): 548-578 (2021) - [j68]Cong Fang, Song Bai, Qianlan Chen, Yu Zhou, Liming Xia, Lixin Qin, Shi Gong, Xudong Xie, Chunhua Zhou, Dandan Tu, Changzheng Zhang, Xiaowu Liu, Weiwei Chen, Xiang Bai, Philip H. S. Torr:
Deep learning for predicting COVID-19 malignant progression. Medical Image Anal. 72: 102096 (2021) - [j67]Shanghua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip H. S. Torr:
Res2Net: A New Multi-Scale Backbone Architecture. IEEE Trans. Pattern Anal. Mach. Intell. 43(2): 652-662 (2021) - [j66]Nan Xue, Song Bai, Fudong Wang, Gui-Song Xia, Tianfu Wu, Liangpei Zhang, Philip H. S. Torr:
Learning Regional Attraction for Line Segment Detection. IEEE Trans. Pattern Anal. Mach. Intell. 43(6): 1998-2013 (2021) - [j65]Song Bai, Yingwei Li, Yuyin Zhou, Qizhu Li, Philip H. S. Torr:
Adversarial Metric Attack and Defense for Person Re-Identification. IEEE Trans. Pattern Anal. Mach. Intell. 43(6): 2119-2126 (2021) - [j64]Song Bai, Feihu Zhang, Philip H. S. Torr:
Hypergraph convolution and hypergraph attention. Pattern Recognit. 110: 107637 (2021) - [c264]Arslan Chaudhry, Albert Gordo, Puneet K. Dokania, Philip H. S. Torr, David Lopez-Paz:
Using Hindsight to Anchor Past Knowledge in Continual Learning. AAAI 2021: 6993-7001 - [c263]Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania:
Mirror Descent View for Neural Network Quantization. AISTATS 2021: 2809-2817 - [c262]Zhao Yang, Yansong Tang, Luca Bertinetto, Hengshuang Zhao, Philip H. S. Torr:
Hierarchical Interaction Network for Video Object Segmentation from Referring Expressions. BMVC 2021: 254 - [c261]Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip H. S. Torr, Li Zhang:
Rethinking Semantic Segmentation From a Sequence-to-Sequence Perspective With Transformers. CVPR 2021: 6881-6890 - [c260]Hongguang Zhang, Piotr Koniusz, Songlei Jian, Hongdong Li, Philip H. S. Torr:
Rethinking Class Relations: Absolute-Relative Supervised and Unsupervised Few-Shot Learning. CVPR 2021: 9432-9441 - [c259]Xiaolong Liu, Yao Hu, Song Bai, Fei Ding, Xiang Bai, Philip H. S. Torr:
Multi-Shot Temporal Event Localization: A Benchmark. CVPR 2021: 12596-12606 - [c258]Oscar Rahnama, Stuart Golodetz, Tommaso Cavallari, Philip H. S. Torr:
Scalable FPGA Median Filtering via a Directional Median Cascade. FCCM 2021: 273 - [c257]Xiaoyu Yue, Shuyang Sun, Zhanghui Kuang, Meng Wei, Philip H. S. Torr, Wayne Zhang, Dahua Lin:
Vision Transformer with Progressive Sampling. ICCV 2021: 377-386 - [c256]Shuyang Sun, Xiaoyu Yue, Xiaojuan Qi, Wanli Ouyang, Victor Prisacariu, Philip H. S. Torr:
Aggregation with Feature Detection. ICCV 2021: 507-516 - [c255]Guangrun Wang, Keze Wang, Guangcong Wang, Philip H. S. Torr, Liang Lin:
Solving Inefficiency of Self-supervised Representation Learning. ICCV 2021: 9485-9495 - [c254]Feihu Zhang, Oliver J. Woodford, Victor Prisacariu, Philip H. S. Torr:
Separable Flow: Learning Motion Cost Volumes for Optical Flow Estimation. ICCV 2021: 10787-10797 - [c253]Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip H. S. Torr, Vladlen Koltun:
Point Transformer. ICCV 2021: 16239-16248 - [c252]Angira Sharma, Naeemullah Khan, Muhammad Mubashar, Ganesh Sundaramoorthi, Philip H. S. Torr:
Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation. ICCVW 2021: 1621-1630 - [c251]Matej Kristan, Jirí Matas, Ales Leonardis, Michael Felsberg, Roman P. Pflugfelder, Joni-Kristian Kämäräinen, Hyung Jin Chang, Martin Danelljan, Luka Cehovin Zajc, Alan Lukezic, Ondrej Drbohlav, Jani Käpylä, Gustav Häger, Song Yan, Jinyu Yang, Zhongqun Zhang, Gustavo Fernández, Mohamed H. Abdelpakey, Goutam Bhat, Llukman Cerkezi, Hakan Cevikalp, Shengyong Chen, Xin Chen, Miao Cheng, Ziyi Cheng, Yu-Chen Chiu, Ozgun Cirakman, Yutao Cui, Kenan Dai, Mohana Murali Dasari, Qili Deng, Xingping Dong, Daniel K. Du, Matteo Dunnhofer, Zhen-Hua Feng, Zhiyong Feng, Zhihong Fu, Shiming Ge, Rama Krishna Gorthi, Yuzhang Gu, Bilge Gunsel, Qing Guo, Filiz Gurkan, Wencheng Han, Yanyan Huang, Felix Järemo Lawin, Shang-Jhih Jhang, Rongrong Ji, Cheng Jiang, Yingjie Jiang, Felix Juefei-Xu, J. Yin, Xiao Ke, Fahad Shahbaz Khan, Byeong Hak Kim, Josef Kittler, Xiangyuan Lan, Jun Ha Lee, Bastian Leibe, Hui Li, Jianhua Li, Xianxian Li, Yuezhou Li, Bo Liu, Chang Liu, Jingen Liu, Li Liu, Qingjie Liu, Huchuan Lu, Wei Lu, Jonathon Luiten, Jie Ma, Ziang Ma, Niki Martinel, Christoph Mayer, Alireza Memarmoghadam, Christian Micheloni, Yuzhen Niu, Danda Pani Paudel, Houwen Peng, Shoumeng Qiu, Aravindh Rajiv, Muhammad Rana, Andreas Robinson, Hasan Saribas, Ling Shao, Mohamed S. Shehata, Furao Shen, Jianbing Shen, Kristian Simonato, Xiaoning Song, Zhangyong Tang, Radu Timofte, Philip H. S. Torr, Chi-Yi Tsai, Bedirhan Uzun, Luc Van Gool, Paul Voigtlaender, Dong Wang, Guangting Wang, Liangliang Wang, Lijun Wang, Limin Wang, Linyuan Wang, Yong Wang, Yunhong Wang, Chenyan Wu, Gangshan Wu, Xiaojun Wu, Fei Xie, Tianyang Xu, Xiang Xu, Wanli Xue, Bin Yan, Wankou Yang, Xiaoyun Yang, Yu Ye, Jun Yin, Chengwei Zhang, Chunhui Zhang, Haitao Zhang, Kaihua Zhang, Kangkai Zhang, Xiaohan Zhang, Xiaolin Zhang, Xinyu Zhang, Zhibin Zhang, Shao-Chuan Zhao, Ming Zhen, Bineng Zhong, Jiawen Zhu, Xuefeng Zhu:
The Ninth Visual Object Tracking VOT2021 Challenge Results. ICCVW 2021: 2711-2738 - [c250]Pau de Jorge, Amartya Sanyal, Harkirat S. Behl, Philip H. S. Torr, Grégory Rogez, Puneet K. Dokania:
Progressive Skeletonization: Trimming more fat from a network at initialization. ICLR 2021 - [c249]Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, Siddharth Narayanaswamy, Tom Rainforth:
Capturing Label Characteristics in VAEs. ICLR 2021 - [c248]Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi:
Understanding the effects of data parallelism and sparsity on neural network training. ICLR 2021 - [c247]Alessandro De Palma, Harkirat S. Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar:
Scaling the Convex Barrier with Active Sets. ICLR 2021 - [c246]Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip H. S. Torr:
How Benign is Benign Overfitting ? ICLR 2021 - [c245]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. ICLR 2021 - [c244]Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson:
FACMAC: Factored Multi-Agent Centralised Policy Gradients. NeurIPS 2021: 12208-12221 - [c243]Jiyang Qi, Yan Gao, Yao Hu, Xinggang Wang, Xiaoyu Liu, Xiang Bai, Serge J. Belongie, Alan L. Yuille, Philip H. S. Torr, Song Bai:
Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge. NeurIPS Datasets and Benchmarks 2021 - [c242]Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip H. S. Torr, Luca Bertinetto:
Do Different Tracking Tasks Require Different Appearance Models? NeurIPS 2021: 726-738 - [c241]Feihu Zhang, Philip H. S. Torr, René Ranftl, Stephan R. Richter:
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning. NeurIPS 2021: 3285-3297 - [c240]Harkirat Singh Behl, M. Pawan Kumar, Philip H. S. Torr, Krishnamurthy Dvijotham:
Overcoming the Convex Barrier for Simplex Inputs. NeurIPS 2021: 4871-4882 - [c239]Keyu Tian, Chen Lin, Ser-Nam Lim, Wanli Ouyang, Puneet K. Dokania, Philip H. S. Torr:
A Continuous Mapping For Augmentation Design. NeurIPS 2021: 13732-13743 - [c238]Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip H. S. Torr, Ling Shao:
You Never Cluster Alone. NeurIPS 2021: 27734-27746 - [i185]Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H. S. Torr, M. Pawan Kumar:
Scaling the Convex Barrier with Sparse Dual Algorithms. CoRR abs/2101.05844 (2021) - [i184]Jiyang Qi, Yan Gao, Yao Hu, Xinggang Wang, Xiaoyu Liu, Xiang Bai, Serge J. Belongie, Alan L. Yuille, Philip H. S. Torr, Song Bai:
Occluded Video Instance Segmentation. CoRR abs/2102.01558 (2021) - [i183]Naeemullah Khan, Angira Sharma, Ganesh Sundaramoorthi, Philip H. S. Torr:
Shape-Tailored Deep Neural Networks. CoRR abs/2102.08497 (2021) - [i182]Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty. CoRR abs/2102.11582 (2021) - [i181]Motasem Alfarra, Juan C. Pérez, Ali K. Thabet, Adel Bibi, Philip H. S. Torr, Bernard Ghanem:
Combating Adversaries with Anti-Adversaries. CoRR abs/2103.14347 (2021) - [i180]Bin Ren, Hao Tang, Fanyang Meng, Runwei Ding, Ling Shao, Philip H. S. Torr, Nicu Sebe:
Cloth Interactive Transformer for Virtual Try-On. CoRR abs/2104.05519 (2021) - [i179]Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. CoRR abs/2104.06718 (2021) - [i178]Guangrun Wang, Keze Wang, Guangcong Wang, Philip H. S. Torr, Liang Lin:
Solving Inefficiency of Self-supervised Representation Learning. CoRR abs/2104.08760 (2021) - [i177]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, N. Siddharth, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. CoRR abs/2104.09937 (2021) - [i176]Yansong Tang, Zhenyu Jiang, Zhenda Xie, Yue Cao, Zheng Zhang, Philip H. S. Torr, Han Hu:
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning. CoRR abs/2105.05838 (2021) - [i175]Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip H. S. Torr, Ling Shao:
You Never Cluster Alone. CoRR abs/2106.01908 (2021) - [i174]Shanghua Gao, Zhong-Yu Li, Ming-Hsuan Yang, Ming-Ming Cheng, Junwei Han, Philip H. S. Torr:
Large-scale Unsupervised Semantic Segmentation. CoRR abs/2106.03149 (2021) - [i173]A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Günes Baydin:
KL Guided Domain Adaptation. CoRR abs/2106.07780 (2021) - [i172]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, N. Siddharth:
Learning Multimodal VAEs through Mutual Supervision. CoRR abs/2106.12570 (2021) - [i171]Motasem Alfarra, Adel Bibi, Naeemullah Khan, Philip H. S. Torr, Bernard Ghanem:
DeformRS: Certifying Input Deformations with Randomized Smoothing. CoRR abs/2107.00996 (2021) - [i170]Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip H. S. Torr, Luca Bertinetto:
Do Different Tracking Tasks Require Different Appearance Models? CoRR abs/2107.02156 (2021) - [i169]Francisco Eiras, Motasem Alfarra, M. Pawan Kumar, Philip H. S. Torr, Puneet K. Dokania, Bernard Ghanem, Adel Bibi:
ANCER: Anisotropic Certification via Sample-wise Volume Maximization. CoRR abs/2107.04570 (2021) - [i168]Shuyang Sun, Xiaoyu Yue, Song Bai, Philip H. S. Torr:
Visual Parser: Representing Part-whole Hierarchies with Transformers. CoRR abs/2107.05790 (2021) - [i167]Samuel Sokota, Christian Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Shimon Whiteson, Jakob N. Foerster:
Implicit Communication as Minimum Entropy Coupling. CoRR abs/2107.08295 (2021) - [i166]