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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
[j87]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)- [j86]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) - [j85]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) - [j84]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) - [j83]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) - [j82]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) - [j81]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) - [j80]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) - [j79]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) - [j78]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) - [j77]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) - [j76]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) - [j75]Francesca Babiloni, Ioannis Marras, Jiankang Deng, Filippos Kokkinos, Matteo Maggioni, Grigorios Chrysos, Philip H. S. Torr, Stefanos Zafeiriou:
Linear Complexity Self-Attention With $3{\mathrm{rd}}$3 rd Order Polynomials. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 12726-12737 (2023) - [j74]Nan Xue, Tianfu Wu, Song Bai, Fu-Dong Wang, Gui-Song Xia, Liangpei Zhang, Philip H. S. Torr:
Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14727-14744 (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) - [c316]Dubing Chen, Yuming Shen, Haofeng Zhang, Philip H. S. Torr:
Deconstructed Generation-Based Zero-Shot Model. AAAI 2023: 295-303 - [c315]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 - [c314]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 - [c313]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 - [c312]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 - [c311]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 - [c310]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 - [c309]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 - [c308]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 - [c307]A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim, Philip H. S. Torr:
TIPI: Test Time Adaptation with Transformation Invariance. CVPR 2023: 24162-24171 - [c306]Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deep Deterministic Uncertainty: A New Simple Baseline. CVPR 2023: 24384-24394 - [c305]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 - [c304]Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal:
How robust is unsupervised representation learning to distribution shift? ICLR 2023 - [c303]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 - [c302]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 - [c301]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 - [c300]Yaoyuan Liang, Zhao Yang, Yansong Tang, Jiashuo Fan, Ziran Li, Jingang Wang, Philip H. S. Torr, Shao-Lun Huang:
LUNA: Language as Continuing Anchors for Referring Expression Comprehension. ACM Multimedia 2023: 5174-5184 - [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 - [i261]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) - [i260]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) - [i259]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) - [i258]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) - [i257]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) - [i256]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) - [i255]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) - [i254]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) - [i253]Haoheng Lan, Jindong Gu, Philip H. S. Torr, Hengshuang Zhao:
Influencer Backdoor Attack on Semantic Segmentation. CoRR abs/2303.12054 (2023) - [i252]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) - [i251]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) - [i250]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) - [i249]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) - [i248]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) - [i247]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) - [i246]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) - [i245]Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, Adel Bibi:
Language Model Tokenizers Introduce Unfairness Between Languages. CoRR abs/2305.15425 (2023) - [i244]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) - [i243]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) - [i242]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) - [i241]Wenqian Yu, Jindong Gu, Zhijiang Li, Philip H. S. Torr:
Reliable Evaluation of Adversarial Transferability. CoRR abs/2306.08565 (2023) - [i240]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) - [i239]Runjia Li, Shuyang Sun, Mohamed Elhoseiny, Philip H. S. Torr:
OxfordTVG-HIC: Can Machine Make Humorous Captions from Images? CoRR abs/2307.11636 (2023) - [i238]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) - [i237]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) - [i236]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) - [i235]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) - [i234]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) - [i233]Jia-Wang Bian, Wenjing Bian, Victor Adrian Prisacariu, Philip H. S. Torr:
PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction. CoRR abs/2310.07449 (2023) - [i232]Luke Marks, Amir Abdullah, Luna Mendez, Rauno Arike, Philip H. S. Torr, Fazl Barez:
Interpreting Reward Models in RLHF-Tuned Language Models Using Sparse Autoencoders. CoRR abs/2310.08164 (2023) - [i231]Jianhao Yuan, Jie Zhang, Shuyang Sun, Philip H. S. Torr, Bo Zhao:
Real-Fake: Effective Training Data Synthesis Through Distribution Matching. CoRR abs/2310.10402 (2023) - [i230]Francisco Eiras, Kemal Oksuz, Adel Bibi, Philip H. S. Torr, Puneet K. Dokania:
Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation. CoRR abs/2310.13479 (2023) - [i229]Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip H. S. Torr:
A Survey on Transferability of Adversarial Examples across Deep Neural Networks. CoRR abs/2310.17626 (2023) - [i228]Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila A. McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann:
Managing AI Risks in an Era of Rapid Progress. CoRR abs/2310.17688 (2023) - [i227]Zifu Wang, Maxim Berman, Amal Rannen Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko:
Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union. CoRR abs/2310.19252 (2023) - [i226]Aleksandar Petrov, Philip H. S. Torr, Adel Bibi:
When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations. CoRR abs/2310.19698 (2023) - [i225]Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim, Bernard Ghanem, Philip H. S. Torr, Adel Bibi:
From Categories to Classifier: Name-Only Continual Learning by Exploring the Web. CoRR abs/2311.11293 (2023) - [i224]Shuo Chen, Zhen Han, Bailan He, Mark Buckley, Philip H. S. Torr, Volker Tresp, Jindong Gu:
Understanding and Improving In-Context Learning on Vision-language Models. CoRR abs/2311.18021 (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