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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
- 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) - [c249]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 - [c248]Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania:
Mirror Descent View for Neural Network Quantization. AISTATS 2021: 2809-2817 - [c247]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 - [c246]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 - [c245]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 - [c244]Oscar Rahnama, Stuart Golodetz, Tommaso Cavallari, Philip H. S. Torr:
Scalable FPGA Median Filtering via a Directional Median Cascade. FCCM 2021: 273 - [c243]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 - [c242]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 - [c241]Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, Siddharth Narayanaswamy, Tom Rainforth:
Capturing Label Characteristics in VAEs. ICLR 2021 - [c240]Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi:
Understanding the effects of data parallelism and sparsity on neural network training. ICLR 2021 - [c239]Alessandro De Palma, Harkirat S. Behl, Rudy R. Bunel, Philip H. S. Torr, M. Pawan Kumar:
Scaling the Convex Barrier with Active Sets. ICLR 2021 - [c238]Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip H. S. Torr:
How Benign is Benign Overfitting ? ICLR 2021 - [c237]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. ICLR 2021 - [i183]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) - [i182]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) - [i181]Naeemullah Khan, Angira Sharma, Ganesh Sundaramoorthi, Philip H. S. Torr:
Shape-Tailored Deep Neural Networks. CoRR abs/2102.08497 (2021) - [i180]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) - [i179]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) - [i178]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) - [i177]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) - [i176]Guangrun Wang, Keze Wang, Guangcong Wang, Philip H. S. Torr, Liang Lin:
Solving Inefficiency of Self-supervised Representation Learning. CoRR abs/2104.08760 (2021) - [i175]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, N. Siddharth, Awni Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. CoRR abs/2104.09937 (2021) - [i174]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) - [i173]Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip H. S. Torr, Ling Shao:
You Never Cluster Alone. CoRR abs/2106.01908 (2021) - [i172]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) - [i171]A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Günes Baydin:
KL Guided Domain Adaptation. CoRR abs/2106.07780 (2021) - [i170]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) - [i169]Motasem Alfarra, Adel Bibi, Naeemullah Khan, Philip H. S. Torr, Bernard Ghanem:
DeformRS: Certifying Input Deformations with Randomized Smoothing. CoRR abs/2107.00996 (2021) - [i168]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) - [i167]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) - [i166]Shuyang Sun, Xiaoyu Yue, Song Bai, Philip H. S. Torr:
Visual Parser: Representing Part-whole Hierarchies with Transformers. CoRR abs/2107.05790 (2021) - [i165]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) - [i164]Lu Qi, Jason Kuen, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip H. S. Torr, Jiaya Jia:
Open-World Entity Segmentation. CoRR abs/2107.14228 (2021) - [i163]Botos Csaba, Xiaojuan Qi, Arslan Chaudhry, Puneet K. Dokania, Philip H. S. Torr:
Multilevel Knowledge Transfer for Cross-Domain Object Detection. CoRR abs/2108.00977 (2021) - [i162]Xiaoyu Yue, Shuyang Sun, Zhanghui Kuang, Meng Wei, Philip H. S. Torr, Wayne Zhang, Dahua Lin:
Vision Transformer with Progressive Sampling. CoRR abs/2108.01684 (2021) - [i161]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. CoRR abs/2108.04226 (2021) - [i160]Shiyu Tang, Ruihao Gong, Yan Wang, Aishan Liu, Jiakai Wang, Xinyun Chen, Fengwei Yu, Xianglong Liu, Dawn Song, Alan L. Yuille, Philip H. S. Torr, Dacheng Tao:
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques. CoRR abs/2109.05211 (2021) - [i159]Andrew Gambardella, Bogdan State, Naeemullah Khan, Leo Tsourides, Philip H. S. Torr, Atilim Günes Baydin:
Detecting and Quantifying Malicious Activity with Simulation-based Inference. CoRR abs/2110.02483 (2021) - [i158]Jishnu Mukhoti, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deep Deterministic Uncertainty for Semantic Segmentation. CoRR abs/2111.00079 (2021) - [i157]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. CoRR abs/2111.07950 (2021) - [i156]Jieneng Chen, Shuyang Sun, Ju He, Philip H. S. Torr, Alan L. Yuille, Song Bai:
TransMix: Attend to Mix for Vision Transformers. CoRR abs/2111.09833 (2021) - [i155]Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr:
Adversarial Examples on Segmentation Models Can be Easy to Transfer. CoRR abs/2111.11368 (2021) - [i154]Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip H. S. Torr, Guoying Zhao:
PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer. CoRR abs/2111.12082 (2021) - [i153]Christian Schröder de Witt, Yongchao Huang, Philip H. S. Torr, Martin Strohmeier:
Fixed Points in Cyber Space: Rethinking Optimal Evasion Attacks in the Age of AI-NIDS. CoRR abs/2111.12197 (2021) - [i152]Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip H. S. Torr:
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation. CoRR abs/2112.02244 (2021) - 2020
- [j63]Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, Adnane Boukhayma, N. Siddharth, Philip H. S. Torr:
DGPose: Deep Generative Models for Human Body Analysis. Int. J. Comput. Vis. 128(5): 1537-1563 (2020) - [j62]Rudy Bunel, Jingyue Lu, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, M. Pawan Kumar:
Branch and Bound for Piecewise Linear Neural Network Verification. J. Mach. Learn. Res. 21: 42:1-42:39 (2020) - [j61]Juan-Manuel Pérez-Rúa, Ondrej Miksik, Tomás Crivelli, Patrick Bouthemy, Philip H. S. Torr, Patrick Pérez:
ROAM: A Rich Object Appearance Model with Application to Rotoscoping. IEEE Trans. Pattern Anal. Mach. Intell. 42(8): 1996-2010 (2020) - [j60]Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord, Julien P. C. Valentin, Victor Adrian Prisacariu, Luigi di Stefano, Philip H. S. Torr:
Real-Time RGB-D Camera Pose Estimation in Novel Scenes Using a Relocalisation Cascade. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2465-2477 (2020) - [j59]Anurag Arnab, Ondrej Miksik, Philip H. S. Torr:
On the Robustness of Semantic Segmentation Models to Adversarial Attacks. IEEE Trans. Pattern Anal. Mach. Intell. 42(12): 3040-3053 (2020) - [c236]Hao Tang, Song Bai, Philip H. S. Torr, Nicu Sebe:
Bipartite Graph Reasoning GANs for Person Image Generation. BMVC 2020 - [c235]Nan Xue, Tianfu Wu, Song Bai, Fudong Wang, Gui-Song Xia, Liangpei Zhang, Philip H. S. Torr:
Holistically-Attracted Wireframe Parsing. CVPR 2020: 2785-2794 - [c234]Li Zhang, Dan Xu, Anurag Arnab, Philip H. S. Torr:
Dynamic Graph Message Passing Networks. CVPR 2020: 3723-3732 - [c233]Victoria Fernández Abrevaya, Adnane Boukhayma, Philip H. S. Torr, Edmond Boyer:
Cross-Modal Deep Face Normals With Deactivable Skip Connections. CVPR 2020: 4978-4988 - [c232]Paul Voigtlaender, Jonathon Luiten, Philip H. S. Torr, Bastian Leibe:
Siam R-CNN: Visual Tracking by Re-Detection. CVPR 2020: 6577-6587 - [c231]Hao Tang, Dan Xu, Yan Yan, Philip H. S. Torr, Nicu Sebe:
Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation. CVPR 2020: 7867-7876 - [c230]Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H. S. Torr:
ManiGAN: Text-Guided Image Manipulation. CVPR 2020: 7877-7886 - [c229]Zhengzhe Liu, Xiaojuan Qi, Philip H. S. Torr:
Global Texture Enhancement for Fake Face Detection in the Wild. CVPR 2020: 8057-8066 - [c228]Qizhu Li, Xiaojuan Qi, Philip H. S. Torr:
Unifying Training and Inference for Panoptic Segmentation. CVPR 2020: 13317-13325 - [c227]Carlo Biffi, Steven McDonagh, Philip H. S. Torr, Ales Leonardis, Sarah Parisot:
Many-Shot from Low-Shot: Learning to Annotate Using Mixed Supervision for Object Detection. ECCV (8) 2020: 35-50 - [c226]Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet:
AutoSimulate: (Quickly) Learning Synthetic Data Generation. ECCV (22) 2020: 255-271 - [c225]Viveka Kulharia, Siddhartha Chandra, Amit Agrawal, Philip H. S. Torr, Ambrish Tyagi:
Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation. ECCV (27) 2020: 290-308 - [c224]Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu, Benjamin W. Wah, Philip H. S. Torr:
Domain-Invariant Stereo Matching Networks. ECCV (2) 2020: 420-439 - [c223]Ameya Prabhu, Philip H. S. Torr, Puneet K. Dokania:
GDumb: A Simple Approach that Questions Our Progress in Continual Learning. ECCV (2) 2020: 524-540 - [c222]Hongguang Zhang, Li Zhang, Xiaojuan Qi, Hongdong Li, Philip H. S. Torr, Piotr Koniusz:
Few-Shot Action Recognition with Permutation-Invariant Attention. ECCV (5) 2020: 525-542 - [c221]Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman P. Pflugfelder, Joni-Kristian Kämäräinen, Martin Danelljan, Luka Cehovin Zajc, Alan Lukezic, Ondrej Drbohlav, Linbo He, Yushan Zhang, Song Yan, Jinyu Yang, Gustavo Fernández, Alexander G. Hauptmann, Alireza Memarmoghadam, Álvaro García-Martín, Andreas Robinson, Anton Varfolomieiev, Awet Haileslassie Gebrehiwot, Bedirhan Uzun, Bin Yan, Bing Li, Chen Qian, Chi-Yi Tsai, Christian Micheloni, Dong Wang, Fei Wang, Fei Xie, Felix Järemo Lawin, Fredrik Gustafsson, Gian Luca Foresti, Goutam Bhat, Guangqi Chen, Haibin Ling, Haitao Zhang, Hakan Cevikalp, Haojie Zhao, Haoran Bai, Hari Chandana Kuchibhotla, Hasan Saribas, Heng Fan, Hossein Ghanei-Yakhdan, Houqiang Li, Houwen Peng, Huchuan Lu, Hui Li, Javad Khaghani, Jesús Bescós, Jianhua Li, Jianlong Fu, Jiaqian Yu, Jingtao Xu, Josef Kittler, Jun Yin, Junhyun Lee, Kaicheng Yu, Kaiwen Liu, Kang Yang, Kenan Dai, Li Cheng, Li Zhang, Lijun Wang, Linyuan Wang, Luc Van Gool, Luca Bertinetto, Matteo Dunnhofer, Miao Cheng, Mohana Murali Dasari, Ning Wang, Pengyu Zhang, Philip H. S. Torr, Qiang Wang, Radu Timofte, Rama Krishna Sai Gorthi, Seokeon Choi, Seyed Mojtaba Marvasti-Zadeh, Shao-Chuan Zhao, Shohreh Kasaei, Shoumeng Qiu, Shuhao Chen, Thomas B. Schön, Tianyang Xu, Wei Lu, Weiming Hu, Wengang Zhou, Xi Qiu, Xiao Ke, Xiao-Jun Wu, Xiaolin Zhang, Xiaoyun Yang, Xuefeng Zhu, Yingjie Jiang, Yingming Wang, Yiwei Chen, Yu Ye, Yuezhou Li, Yuncon Yao, Yunsung Lee, Yuzhang Gu, Zezhou Wang, Zhangyong Tang, Zhen-Hua Feng, Zhijun Mai, Zhipeng Zhang, Zhirong Wu, Ziang Ma:
The Eighth Visual Object Tracking VOT2020 Challenge Results. ECCV Workshops (5) 2020: 547-601 - [c220]Feihu Zhang, Jin Fang, Benjamin W. Wah, Philip H. S. Torr:
Deep FusionNet for Point Cloud Semantic Segmentation. ECCV (24) 2020: 644-663 - [c219]Hao Tang, Song Bai, Li Zhang, Philip H. S. Torr, Nicu Sebe:
XingGAN for Person Image Generation. ECCV (25) 2020: 717-734 - [c218]Oscar Rahnama, Tommaso Cavallari, Philip H. S. Torr, Stuart Golodetz:
Scalable FPGA Median Filtering using Multiple Efficient Passes. FPGA 2020: 313 - [c217]Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr:
A Signal Propagation Perspective for Pruning Neural Networks at Initialization. ICLR 2020 - [c216]Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania:
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs. ICLR 2020 - [c215]Francesco Pinto, Andrea Romanoni, Matteo Matteucci, Philip H. S. Torr:
SECI-GAN: Semantic and Edge Completion for dynamic objects removal. ICPR 2020: 10441-10448 - [c214]Feihu Zhang, Chenye Guan, Jin Fang, Song Bai, Ruigang Yang, Philip H. S. Torr, Victor Prisacariu:
Instance Segmentation of LiDAR Point Clouds. ICRA 2020: 9448-9455 - [c213]Harkirat Singh Behl, Mohammad Najafi, Anurag Arnab, Philip H. S. Torr:
Meta-Learning Deep Visual Words for Fast Video Object Segmentation. IROS 2020: 8484-8491 - [c212]Arslan Chaudhry, Naeemullah Khan, Puneet K. Dokania, Philip H. S. Torr:
Continual Learning in Low-rank Orthogonal Subspaces. NeurIPS 2020 - [c211]Arnab Ghosh, Harkirat S. Behl, Emilien Dupont, Philip H. S. Torr, Vinay Namboodiri:
STEER : Simple Temporal Regularization For Neural ODE. NeurIPS 2020 - [c210]Bowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz:
Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation. NeurIPS 2020 - [c209]Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip H. S. Torr, Puneet K. Dokania:
Calibrating Deep Neural Networks using Focal Loss. NeurIPS 2020 - [c208]Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Lagrangian Decomposition for Neural Network Verification. UAI 2020: 370-379 - [c207]Yao Lu, Jack Valmadre, Heng Wang, Juho Kannala, Mehrtash Harandi, Philip H. S. Torr:
Devon: Deformable Volume Network for Learning Optical Flow. WACV 2020: 2694-2702 - [i151]Hongguang Zhang, Philip H. S. Torr, Piotr Koniusz:
Few-shot Learning with Multi-scale Self-supervision. CoRR abs/2001.01600 (2020) - [i150]Hongguang Zhang, Li Zhang, Xiaojuan Qi, Hongdong Li, Philip H. S. Torr, Piotr Koniusz:
Few-shot Action Recognition via Improved Attention with Self-supervision. CoRR abs/2001.03905 (2020) - [i149]Hongguang Zhang, Philip H. S. Torr, Hongdong Li, Songlei Jian, Piotr Koniusz:
Rethinking Class Relations: Absolute-relative Few-shot Learning. CoRR abs/2001.03919 (2020) - [i148]Qizhu Li, Xiaojuan Qi, Philip H. S. Torr:
Unifying Training and Inference for Panoptic Segmentation. CoRR abs/2001.04982 (2020) - [i147]Zhengzhe Liu, Xiaojuan Qi, Jiaya Jia, Philip H. S. Torr:
Global Texture Enhancement for Fake Face Detection in the Wild. CoRR abs/2002.00133 (2020) - [i146]Hao Tang, Dan Xu, Yan Yan, Jason J. Corso, Philip H. S. Torr, Nicu Sebe:
Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation. CoRR abs/2002.01048 (2020) - [i145]Bowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz:
Image-to-Image Translation with Text Guidance. CoRR abs/2002.05235 (2020) - [i144]Arslan Chaudhry, Albert Gordo, Puneet K. Dokania, Philip H. S. Torr, David Lopez-Paz:
Using Hindsight to Anchor Past Knowledge in Continual Learning. CoRR abs/2002.08165 (2020) - [i143]Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip H. S. Torr, Puneet K. Dokania:
Calibrating Deep Neural Networks using Focal Loss. CoRR abs/2002.09437 (2020) - [i142]Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar:
Lagrangian Decomposition for Neural Network Verification. CoRR abs/2002.10410 (2020) - [i141]Nan Xue, Tianfu Wu, Song Bai, Fudong Wang, Gui-Song Xia, Liangpei Zhang, Philip H. S. Torr:
Holistically-Attracted Wireframe Parsing. CoRR abs/2003.01663 (2020) - [i140]Christian Schröder de Witt, Bei Peng, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Böhmer, Shimon Whiteson:
Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control. CoRR abs/2003.06709 (2020) - [i139]Victoria Fernández Abrevaya, Adnane Boukhayma, Philip H. S. Torr, Edmond Boyer:
Cross-modal Deep Face Normals with Deactivable Skip Connections. CoRR abs/2003.09691 (2020) - [i138]Namhoon Lee, Philip H. S. Torr, Martin Jaggi:
Data Parallelism in Training Sparse Neural Networks. CoRR abs/2003.11316 (2020) - [i137]Hao Tang, Xiaojuan Qi, Dan Xu, Philip H. S. Torr, Nicu Sebe:
Edge Guided GANs with Semantic Preserving for Semantic Image Synthesis. CoRR abs/2003.13898 (2020) - [i136]Daniela Massiceti, Viveka Kulharia, Puneet K. Dokania, N. Siddharth, Philip H. S. Torr:
A Revised Generative Evaluation of Visual Dialogue. CoRR abs/2004.09272 (2020) - [i135]Christian Schröder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Robert Zinkov, Puneet K. Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip H. S. Torr, Atilim Günes Baydin:
Simulation-Based Inference for Global Health Decisions. CoRR abs/2005.07062 (2020) - [i134]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. CoRR abs/2006.09081 (2020) - [i133]Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, N. Siddharth, Tom Rainforth:
Rethinking Semi-Supervised Learning in VAEs. CoRR abs/2006.10102 (2020) - [i132]Arnab Ghosh, Harkirat Singh Behl, Emilien Dupont, Philip H. S. Torr, Vinay Namboodiri:
STEER : Simple Temporal Regularization For Neural ODEs. CoRR abs/2006.10711 (2020) - [i131]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. CoRR abs/2007.01179 (2020) - [i130]Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip H. S. Torr:
How benign is benign overfitting? CoRR abs/2007.04028 (2020) - [i129]Minqi Jiang, Jelena Luketina, Nantas Nardelli, Pasquale Minervini, Philip H. S. Torr, Shimon Whiteson, Tim Rocktäschel:
WordCraft: An Environment for Benchmarking Commonsense Agents. CoRR abs/2007.09185 (2020) - [i128]Hao Tang, Song Bai, Li Zhang, Philip H. S. Torr, Nicu Sebe:
XingGAN for Person Image Generation. CoRR abs/2007.09278 (2020) - [i127]Hao Tang, Song Bai, Philip H. S. Torr, Nicu Sebe:
Bipartite Graph Reasoning GANs for Person Image Generation. CoRR abs/2008.04381 (2020) - [i126]Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet:
AutoSimulate: (Quickly) Learning Synthetic Data Generation. CoRR abs/2008.08424 (2020) - [i125]Carlo Biffi, Steven McDonagh, Philip H. S. Torr, Ales Leonardis, Sarah Parisot:
Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection. CoRR abs/2008.09694 (2020) - [i124]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. CoRR abs/2009.07736 (2020) - [i123]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. CoRR abs/2010.05099 (2020) - [i122]Arslan Chaudhry, Naeemullah Khan, Puneet K. Dokania, Philip H. S. Torr:
Continual Learning in Low-rank Orthogonal Subspaces. CoRR abs/2010.11635 (2020) - [i121]Bowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz:
Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation. CoRR abs/2010.12136 (2020) - [i120]Angira Sharma, Naeemullah Khan, Ganesh Sundaramoorthi, Philip H. S. Torr:
Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation. CoRR abs/2010.14793 (2020) - [i119]Christian Schröder de Witt, Tarun Gupta, Denys Makoviichuk, Viktor Makoviychuk, Philip H. S. Torr, Mingfei Sun, Shimon Whiteson:
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge? CoRR abs/2011.09533 (2020) - [i118]Shuyang Sun, Liang Chen, Gregory G. Slabaugh, Philip H. S. Torr:
Learning to Sample the Most Useful Training Patches from Images. CoRR abs/2011.12097 (2020) - [i117]Motasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem:
Data Dependent Randomized Smoothing. CoRR abs/2012.04351 (2020) - [i116]