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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
[j85]Hao Tang
, Ling Shao, Philip H. S. Torr, Nicu Sebe:
Bipartite Graph Reasoning GANs for Person Pose and Facial Image Synthesis. Int. J. Comput. Vis. 131(3): 644-658 (2023)- [j84]Ming-Ming Cheng, Peng-Tao Jiang, Linghao Han, Liang Wang, Philip H. S. Torr:
Deeply Explain CNN Via Hierarchical Decomposition. Int. J. Comput. Vis. 131(5): 1091-1105 (2023) - [j83]Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Yawen Cui, Jiehua Zhang, Philip H. S. Torr, Guoying Zhao:
PhysFormer++: Facial Video-Based Physiological Measurement with SlowFast Temporal Difference Transformer. Int. J. Comput. Vis. 131(6): 1307-1330 (2023) - [j82]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) - [j81]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) - [j80]Weiming Hu, Qiang Wang, Li Zhang, Luca Bertinetto, Philip H. S. Torr:
SiamMask: A Framework for Fast Online Object Tracking and Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3072-3089 (2023) - [j79]Li Zhang, Mohan Chen, Anurag Arnab, Xiangyang Xue, Philip H. S. Torr:
Dynamic Graph Message Passing Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5712-5730 (2023) - [j78]Hao Tang, Philip H. S. Torr, Nicu Sebe:
Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 6055-6071 (2023) - [j77]Song Bai, Philip H. S. Torr, Ranjay Krishna, Li Fei-Fei, Abhinav Gupta, Song-Chun Zhu:
Guest Editorial: Introduction to the Special Section on Graphs in Vision and Pattern Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 6867-6869 (2023) - [j76]Shanghua Gao, Zhong-Yu Li, Ming-Hsuan Yang, Ming-Ming Cheng, Junwei Han, Philip H. S. Torr:
Large-Scale Unsupervised Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7457-7476 (2023) - [j75]Lu Qi, Jason Kuen, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Philip H. S. Torr, Zhe Lin, Jiaya Jia:
Open World Entity Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8743-8756 (2023) - [j74]Shuyang Sun, Xiaoyu Yue, Hengshuang Zhao, Philip H. S. Torr, Song Bai:
Patch-Based Separable Transformer for Visual Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 9241-9247 (2023) - [j73]Hao Tang, Hong Liu, Dan Xu, Philip H. S. Torr, Nicu Sebe:
AttentionGAN: Unpaired Image-to-Image Translation Using Attention-Guided Generative Adversarial Networks. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1972-1987 (2023) - [c315]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Deconstructed Generation-Based Zero-Shot Model. AAAI 2023: 295-303 - [c314]Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip H. S. Torr:
Semantics-Aware Dynamic Localization and Refinement for Referring Image Segmentation. AAAI 2023: 3222-3230 - [c313]Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Sample-Dependent Adaptive Temperature Scaling for Improved Calibration. AAAI 2023: 14919-14926 - [c312]Hasan Abed Al Kader Hammoud, Adel Bibi, Philip H. S. Torr, Bernard Ghanem:
Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs. CVPR Workshops 2023: 2338-2345 - [c311]Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet K. Dokania, Philip H. S. Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi:
Computationally Budgeted Continual Learning: What Does Matter? CVPR 2023: 3698-3707 - [c310]Kejie Li, Jia-Wang Bian, Robert Castle, Philip H. S. Torr, Victor Adrian Prisacariu:
MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices. CVPR 2023: 4892-4901 - [c309]Pau de Jorge, Riccardo Volpi, Philip H. S. Torr, Grégory Rogez:
Reliability in Semantic Segmentation: Are we on the Right Track? CVPR 2023: 7173-7182 - [c308]Yasir Ghunaim, Adel Bibi, Kumail Alhamoud, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Ameya Prabhu, Philip H. S. Torr, Bernard Ghanem:
Real-Time Evaluation in Online Continual Learning: A New Hope. CVPR 2023: 11888-11897 - [c307]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. CVPR 2023: 19413-19423 - [c306]A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim, Philip H. S. Torr:
TIPI: Test Time Adaptation with Transformation Invariance. CVPR 2023: 24162-24171 - [c305]Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deep Deterministic Uncertainty: A New Simple Baseline. CVPR 2023: 24384-24394 - [c304]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? ICLR 2023 - [c303]Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal:
How robust is unsupervised representation learning to distribution shift? ICLR 2023 - [c302]Yibo Yang, Haobo Yuan, Xiangtai Li, Zhouchen Lin, Philip H. S. Torr, Dacheng Tao:
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning. ICLR 2023 - [c301]Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim:
Graph Inductive Biases in Transformers without Message Passing. ICML 2023: 23321-23337 - [c300]Aleksandar Petrov, Francisco Eiras, Amartya Sanyal, Philip H. S. Torr, Adel Bibi:
Certifying Ensembles: A General Certification Theory with S-Lipschitzness. ICML 2023: 27709-27736 - [c299]Taras Rumezhak, Francisco Girbal Eiras, Philip H. S. Torr, Adel Bibi:
RANCER: Non-Axis Aligned Anisotropic Certification with Randomized Smoothing. WACV 2023: 4661-4669 - [i251]Yasir Ghunaim, Adel Bibi, Kumail Alhamoud, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Ameya Prabhu, Philip H. S. Torr, Bernard Ghanem:
Real-Time Evaluation in Online Continual Learning: A New Paradigm. CoRR abs/2302.01047 (2023) - [i250]Henghui Ding, Chang Liu, Shuting He, Xudong Jiang, Philip H. S. Torr, Song Bai:
MOSE: A New Dataset for Video Object Segmentation in Complex Scenes. CoRR abs/2302.01872 (2023) - [i249]Yibo Yang, Haobo Yuan, Xiangtai Li, Zhouchen Lin, Philip H. S. Torr, Dacheng Tao:
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning. CoRR abs/2302.03004 (2023) - [i248]Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Yawen Cui, Jiehua Zhang, Philip H. S. Torr, Guoying Zhao:
PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer. CoRR abs/2302.03548 (2023) - [i247]Kejie Li, Jia-Wang Bian, Robert Castle, Philip H. S. Torr, Victor Adrian Prisacariu:
MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices. CoRR abs/2303.01932 (2023) - [i246]Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip H. S. Torr:
Semantics-Aware Dynamic Localization and Refinement for Referring Image Segmentation. CoRR abs/2303.06345 (2023) - [i245]Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet K. Dokania, Philip H. S. Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi:
Computationally Budgeted Continual Learning: What Does Matter? CoRR abs/2303.11165 (2023) - [i244]Pau de Jorge, Riccardo Volpi, Philip H. S. Torr, Grégory Rogez:
Reliability in Semantic Segmentation: Are We on the Right Track? CoRR abs/2303.11298 (2023) - [i243]Haoheng Lan, Jindong Gu, Philip H. S. Torr, Hengshuang Zhao:
Influencer Backdoor Attack on Semantic Segmentation. CoRR abs/2303.12054 (2023) - [i242]Hasan Abed Al Kader Hammoud, Adel Bibi, Philip H. S. Torr, Bernard Ghanem:
Don't FREAK Out: A Frequency-Inspired Approach to Detecting Backdoor Poisoned Samples in DNNs. CoRR abs/2303.13211 (2023) - [i241]Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip H. S. Torr, Yao Qin:
Towards Robust Prompts on Vision-Language Models. CoRR abs/2304.08479 (2023) - [i240]Ondrej Bohdal, Timothy M. Hospedales, Philip H. S. Torr, Fazl Barez:
Fairness in AI and Its Long-Term Implications on Society. CoRR abs/2304.09826 (2023) - [i239]Aleksandar Petrov, Francisco Eiras, Amartya Sanyal, Philip H. S. Torr, Adel Bibi:
Certifying Ensembles: A General Certification Theory with S-Lipschitzness. CoRR abs/2304.13019 (2023) - [i238]Ameya Prabhu, Zhipeng Cai, Puneet K. Dokania, Philip H. S. Torr, Vladlen Koltun, Ozan Sener:
Online Continual Learning Without the Storage Constraint. CoRR abs/2305.09253 (2023) - [i237]Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip H. S. Torr, Adel Bibi, Bernard Ghanem:
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? CoRR abs/2305.09275 (2023) - [i236]Francisco Eiras, Adel Bibi, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, Philip H. S. Torr, M. Pawan Kumar:
Provably Correct Physics-Informed Neural Networks. CoRR abs/2305.10157 (2023) - [i235]Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, Adel Bibi:
Language Model Tokenizers Introduce Unfairness Between Languages. CoRR abs/2305.15425 (2023) - [i234]Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim:
Graph Inductive Biases in Transformers without Message Passing. CoRR abs/2305.17589 (2023) - [i233]Shuo Chen, Jindong Gu, Zhen Han, Yunpu Ma, Philip H. S. Torr, Volker Tresp:
Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models. CoRR abs/2306.02080 (2023) - [i232]Tom A. Lamb, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, M. Pawan Kumar, Philip H. S. Torr, Francisco Eiras:
Faithful Knowledge Distillation. CoRR abs/2306.04431 (2023) - [i231]Wenqian Yu, Jindong Gu, Zhijiang Li, Philip H. S. Torr:
Reliable Evaluation of Adversarial Transferability. CoRR abs/2306.08565 (2023) - [i230]Shuyang Sun, Weijun Wang, Qihang Yu, Andrew G. Howard, Philip H. S. Torr, Liang-Chieh Chen:
ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation. CoRR abs/2306.17319 (2023) - [i229]Runjia Li, Shuyang Sun, Mohamed Elhoseiny, Philip H. S. Torr:
OxfordTVG-HIC: Can Machine Make Humorous Captions from Images? CoRR abs/2307.11636 (2023) - [i228]Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip H. S. Torr:
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models. CoRR abs/2307.12980 (2023) - [i227]Yibo Yang, Haobo Yuan, Xiangtai Li, Jianlong Wu, Lefei Zhang, Zhouchen Lin, Philip H. S. Torr, Dacheng Tao, Bernard Ghanem:
Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants. CoRR abs/2308.01746 (2023) - [i226]Guangyi Chen, Xiao Liu, Guangrun Wang, Kun Zhang, Philip H. S. Torr, Xiao-Ping Zhang, Yansong Tang:
Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer. CoRR abs/2308.08414 (2023) - [i225]Jishnu Mukhoti, Yarin Gal, Philip H. S. Torr, Puneet K. Dokania:
Fine-tuning can cripple your foundation model; preserving features may be the solution. CoRR abs/2308.13320 (2023) - [i224]Jindong Gu, Fangyun Wei, Philip H. S. Torr, Han Hu:
Exploring Non-additive Randomness on ViT against Query-Based Black-Box Attacks. CoRR abs/2309.06438 (2023) - 2022
- [j72]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) - [j71]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) - [j70]Francisco Eiras, Motasem Alfarra, Philip H. S. Torr, M. Pawan Kumar, Puneet K. Dokania, Bernard Ghanem, Adel Bibi:
ANCER: Anisotropic Certification via Sample-wise Volume Maximization. Trans. Mach. Learn. Res. 2022 (2022) - [c298]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 - [c297]Motasem Alfarra, Adel Bibi, Naeemullah Khan, Philip H. S. Torr, Bernard Ghanem:
DeformRS: Certifying Input Deformations with Randomized Smoothing. AAAI 2022: 6001-6009 - [c296]Hongguang Zhang, Philip H. S. Torr, Piotr Koniusz:
Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer. ACCV (5) 2022: 3-20 - [c295]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 - [c294]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Image-to-Image Translation with Text Guidance. BMVC 2022: 581 - [c293]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Memory-Driven Text-to-Image Generation. BMVC 2022: 726 - [c292]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 - [c291]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 - [c290]Guangrun Wang, Yansong Tang, Liang Lin, Philip H. S. Torr:
Semantic-Aware Auto-Encoders for Self-supervised Representation Learning. CVPR 2022: 9654-9665 - [c289]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 - [c288]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 - [c287]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 - [c286]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 - [c285]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 - [c284]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 - [c283]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 - [c282]Francesco Pinto, Philip H. S. Torr, Puneet K. Dokania:
An Impartial Take to the CNN vs Transformer Robustness Contest. ECCV (13) 2022: 466-480 - [c281]Botos Csaba, Adel Bibi, Yanwei Li, Philip H. S. Torr, Ser-Nam Lim:
Diversified Dynamic Routing for Vision Tasks. ECCV Workshops (4) 2022: 756-772 - [c280]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, Siddharth Narayanaswamy:
Learning Multimodal VAEs through Mutual Supervision. ICLR 2022 - [c279]A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Gunes Baydin:
KL Guided Domain Adaptation. ICLR 2022 - [c278]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, Siddharth Narayanaswamy, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. ICLR 2022 - [c277]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. ICML 2022: 20026-20040 - [c276]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 - [c275]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Zero-Shot Logit Adjustment. IJCAI 2022: 813-819 - [c274]Jiaguo Yu, Yuming Shen, Menghan Wang, Haofeng Zhang, Philip H. S. Torr:
Learning to Hash Naturally Sorts. IJCAI 2022: 1587-1593 - [c273]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 - [c272]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Clustering Generative Adversarial Networks for Story Visualization. ACM Multimedia 2022: 769-778 - [c271]Pau de Jorge Aranda, 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. NeurIPS 2022 - [c270]Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip H. S. Torr, Liang Lin:
Structure-Preserving 3D Garment Modeling with Neural Sewing Machines. NeurIPS 2022 - [c269]Tim Franzmeyer, Philip H. S. Torr, João F. Henriques:
Learn what matters: cross-domain imitation learning with task-relevant embeddings. NeurIPS 2022 - [c268]A. Tuan Nguyen, Philip H. S. Torr, Ser Nam Lim:
FedSR: A Simple and Effective Domain Generalization Method for Federated Learning. NeurIPS 2022 - [c267]Francesco Pinto, Harry Yang, Ser Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness. NeurIPS 2022 - [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 - [i223]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) - [i222]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) - [i221]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. CoRR abs/2201.13100 (2022) - [i220]Yuming Shen, Jiaguo Yu, Haofeng Zhang, Philip H. S. Torr, Menghan Wang:
Learning to Hash Naturally Sorts. CoRR abs/2201.13322 (2022) - [i219]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) - [i218]Atilim Günes Baydin, Barak A. Pearlmutter, Don Syme, Frank Wood, Philip H. S. Torr:
Gradients without Backpropagation. CoRR abs/2202.08587 (2022) - [i217]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) - [i216]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) - [i215]A. Tuan Nguyen, Ser Nam Lim, Philip H. S. Torr:
Task-Agnostic Robust Representation Learning. CoRR abs/2203.07596 (2022) - [i214]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) - [i213]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) - [i212]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) - [i211]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) - [i210]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Zero-Shot Logit Adjustment. CoRR abs/2204.11822 (2022) - [i209]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) - [i208]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) - [i207]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) - [i206]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) - [i205]