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ORCIDTimothy M. Hospedales
Person information
- affiliation: Queen Mary University of London, UK
- affiliation (PhD 2008): University of Edinburgh, UK
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2020 – today
- 2023
[j36]Peng Xu
, Timothy M. Hospedales, Qiyue Yin, Yi-Zhe Song, Tao Xiang, Liang Wang:
Deep Learning for Free-Hand Sketch: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 285-312 (2023)- [j35]Zhihe Lu, Da Li, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Uncertainty-Aware Source-Free Domain Adaptive Semantic Segmentation. IEEE Trans. Image Process. 32: 4664-4676 (2023) - [c151]Dongliang Chang, Yujun Tong, Ruoyi Du, Timothy M. Hospedales, Yi-Zhe Song, Zhanyu Ma:
An Erudite Fine-Grained Visual Classification Model. CVPR 2023: 7268-7277 - [c150]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CVPR 2023: 7693-7703 - [c149]Ruoyi Du, Dongliang Chang, Kongming Liang, Timothy M. Hospedales, Yi-Zhe Song, Zhanyu Ma:
On-the-Fly Category Discovery. CVPR 2023: 11691-11700 - [c148]Fengyin Lin, Mingkang Li, Da Li, Timothy M. Hospedales, Yi-Zhe Song, Yonggang Qi:
Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. CVPR 2023: 23349-23358 - [c147]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
ChiroDiff: Modelling chirographic data with Diffusion Models. ICLR 2023 - [c146]Ruchika Chavhan, Jan Stuehmer, Calum Heggan, Mehrdad Yaghoobi, Timothy M. Hospedales:
Amortised Invariance Learning for Contrastive Self-Supervision. ICLR 2023 - [c145]Cristina Cornelio, Jan Stuehmer, Shell Xu Hu, Timothy M. Hospedales:
Learning where and when to reason in neuro-symbolic inference. ICLR 2023 - [c144]Minyoung Kim, Da Li, Timothy M. Hospedales:
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. ICLR 2023 - [c143]Yongshuo Zong, Yongxin Yang, Timothy M. Hospedales:
MEDFAIR: Benchmarking Fairness for Medical Imaging. ICLR 2023 - [c142]Cristina Cornelio, Jan Stühmer, Shell Xu Hu, Timothy M. Hospedales:
Learning Where and When to Reason in Neuro-Symbolic Inference. NeSy 2023: 411-412 - [c141]Yongxin Yang, Timothy M. Hospedales:
On Calibration of Mathematical Finance Models by Hypernetworks. ECML/PKDD (6) 2023: 227-242 - [c140]Yongxin Yang, Timothy M. Hospedales:
Mixture of Normalizing Flows for European Option Pricing. UAI 2023: 2390-2399 - [c139]Mustafa Taha Koçyigit, Timothy M. Hospedales, Hakan Bilen:
Accelerating Self-Supervised Learning via Efficient Training Strategies. WACV 2023: 5643-5653 - [i145]Minyoung Kim, Da Li, Timothy M. Hospedales:
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. CoRR abs/2302.12047 (2023) - [i144]Ruchika Chavhan, Henry Gouk, Jan Stuehmer, Calum Heggan, Mehrdad Yaghoobi, Timothy M. Hospedales:
Amortised Invariance Learning for Contrastive Self-Supervision. CoRR abs/2302.12712 (2023) - [i143]Fengyin Lin, Mingkang Li, Da Li, Timothy M. Hospedales, Yi-Zhe Song, Yonggang Qi:
Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style. CoRR abs/2303.14348 (2023) - [i142]Leonardo Iurada, Silvia Bucci, Timothy M. Hospedales, Tatiana Tommasi:
Fairness meets Cross-Domain Learning: a new perspective on Models and Metrics. CoRR abs/2303.14411 (2023) - [i141]Yongshuo Zong, Oisin Mac Aodha, Timothy M. Hospedales:
Self-Supervised Multimodal Learning: A Survey. CoRR abs/2304.01008 (2023) - [i140]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
ChiroDiff: Modelling chirographic data with Diffusion Models. CoRR abs/2304.03785 (2023) - [i139]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) - [i138]Minyoung Kim, Timothy M. Hospedales:
FedHB: Hierarchical Bayesian Federated Learning. CoRR abs/2305.04979 (2023) - [i137]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CoRR abs/2305.07625 (2023) - [i136]Raman Dutt, Linus Ericsson, Pedro Sanchez, Sotirios A. Tsaftaris, Timothy M. Hospedales:
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity. CoRR abs/2305.08252 (2023) - [i135]Calum Heggan, Timothy M. Hospedales, Sam Budgett, Mehrdad Yaghoobi:
MT-SLVR: Multi-Task Self-Supervised Learning for Transformation In(Variant) Representations. CoRR abs/2305.17191 (2023) - [i134]Panagiotis Eustratiadis, Lukasz Dudziak, Da Li, Timothy M. Hospedales:
Neural Fine-Tuning Search for Few-Shot Learning. CoRR abs/2306.09295 (2023) - [i133]Minyoung Kim, Timothy M. Hospedales:
A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning. CoRR abs/2306.09702 (2023) - [i132]Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues:
Impact of Noise on Calibration and Generalisation of Neural Networks. CoRR abs/2306.17630 (2023) - [i131]Luísa Shimabucoro, Timothy M. Hospedales, Henry Gouk:
Evaluating the Evaluators: Are Current Few-Shot Learning Benchmarks Fit for Purpose? CoRR abs/2307.02732 (2023) - [i130]Ondrej Bohdal, Da Li, Timothy M. Hospedales:
Feed-Forward Source-Free Domain Adaptation via Class Prototypes. CoRR abs/2307.10787 (2023) - [i129]Ondrej Bohdal, Da Li, Timothy M. Hospedales:
Label Calibration for Semantic Segmentation Under Domain Shift. CoRR abs/2307.10842 (2023) - [i128]Linus Ericsson, Da Li, Timothy M. Hospedales:
Better Practices for Domain Adaptation. CoRR abs/2309.03879 (2023) - [i127]Minyoung Kim, Timothy M. Hospedales:
BayesDLL: Bayesian Deep Learning Library. CoRR abs/2309.12928 (2023) - [i126]Yongshuo Zong, Tingyang Yu, Bingchen Zhao, Ruchika Chavhan, Timothy M. Hospedales:
Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations. CoRR abs/2310.01651 (2023) - [i125]Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
FedL2P: Federated Learning to Personalize. CoRR abs/2310.02420 (2023) - [i124]Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy M. Hospedales:
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis. CoRR abs/2310.05055 (2023) - [i123]Fady Rezk, Antreas Antoniou, Henry Gouk, Timothy M. Hospedales:
Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months. CoRR abs/2310.18191 (2023) - [i122]Ruolin Yang, Da Li, Conghui Hu, Timothy M. Hospedales, Honggang Zhang, Yi-Zhe Song:
Sketch-based Video Object Segmentation: Benchmark and Analysis. CoRR abs/2311.07261 (2023) - [i121]Ruoyi Du, Dongliang Chang, Timothy M. Hospedales, Yi-Zhe Song, Zhanyu Ma:
DemoFusion: Democratising High-Resolution Image Generation With No $$$. CoRR abs/2311.16973 (2023) - 2022
- [j34]Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, Amos J. Storkey:
Meta-Learning in Neural Networks: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5149-5169 (2022) - [j33]Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales:
Self-Supervised Representation Learning: Introduction, advances, and challenges. IEEE Signal Process. Mag. 39(3): 42-62 (2022) - [j32]Marija Jegorova, Stéphane Doncieux, Timothy M. Hospedales:
Behavioral Repertoire via Generative Adversarial Policy Networks. IEEE Trans. Cogn. Dev. Syst. 14(4): 1344-1355 (2022) - [c138]Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M. Hospedales, Yi-Zhe Song:
Towards Unsupervised Sketch-based Image Retrieval. BMVC 2022: 224 - [c137]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Why Do Self-Supervised Models Transfer? On the Impact of Invariance on Downstream Tasks. BMVC 2022: 509 - [c136]Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales:
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CVPR 2022: 9058-9067 - [c135]Calum Heggan, Sam Budgett, Timothy M. Hospedales, Mehrdad Yaghoobi:
MetaAudio: A Few-Shot Audio Classification Benchmark. ICANN (1) 2022: 219-230 - [c134]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
SketchODE: Learning neural sketch representation in continuous time. ICLR 2022 - [c133]Lucas Deecke, Timothy M. Hospedales, Hakan Bilen:
Visual Representation Learning over Latent Domains. ICLR 2022 - [c132]Haebeom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy M. Hospedales, Sung Ju Hwang:
Online Hyperparameter Meta-Learning with Hypergradient Distillation. ICLR 2022 - [c131]Boyan Gao, Henry Gouk, Yongxin Yang, Timothy M. Hospedales:
Loss Function Learning for Domain Generalization by Implicit Gradient. ICML 2022: 7002-7016 - [c130]Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Fisher SAM: Information Geometry and Sharpness Aware Minimisation. ICML 2022: 11148-11161 - [c129]Miguel Jaques, Martin Asenov, Michael Burke, Timothy M. Hospedales:
Vision-based System Identification and 3D Keypoint Discovery using Dynamics Constraints. L4DC 2022: 316-329 - [i120]Da Li, Henry Gouk, Timothy M. Hospedales:
Finding lost DG: Explaining domain generalization via model complexity. CoRR abs/2202.00563 (2022) - [i119]Boyan Gao, Henry Gouk, Haebeom Lee, Timothy M. Hospedales:
Meta Mirror Descent: Optimiser Learning for Fast Convergence. CoRR abs/2203.02711 (2022) - [i118]Calum Heggan, Sam Budgett, Timothy M. Hospedales, Mehrdad Yaghoobi:
MetaAudio: A Few-Shot Audio Classification Benchmark. CoRR abs/2204.02121 (2022) - [i117]Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales:
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CoRR abs/2204.07305 (2022) - [i116]Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Fisher SAM: Information Geometry and Sharpness Aware Minimisation. CoRR abs/2206.04920 (2022) - [i115]Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Feed-Forward Source-Free Latent Domain Adaptation via Cross-Attention. CoRR abs/2207.07624 (2022) - [i114]Ruchika Chavhan, Henry Gouk, Jan Stühmer, Timothy M. Hospedales:
HyperInvariances: Amortizing Invariance Learning. CoRR abs/2207.08304 (2022) - [i113]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Attacking Adversarial Defences by Smoothing the Loss Landscape. CoRR abs/2208.00862 (2022) - [i112]Yongshuo Zong, Yongxin Yang, Timothy M. Hospedales:
MEDFAIR: Benchmarking Fairness for Medical Imaging. CoRR abs/2210.01725 (2022) - [i111]Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales:
Federated Learning for Inference at Anytime and Anywhere. CoRR abs/2212.04084 (2022) - [i110]Mustafa Taha Koçyigit, Timothy M. Hospedales, Hakan Bilen:
Accelerating Self-Supervised Learning via Efficient Training Strategies. CoRR abs/2212.05611 (2022) - [i109]Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. CoRR abs/2212.07886 (2022) - 2021
- [j31]Qian Yu, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Fine-Grained Instance-Level Sketch-Based Image Retrieval. Int. J. Comput. Vis. 129(2): 484-500 (2021) - [j30]Peng Xu, Kun Liu, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma, Jun Guo, Yi-Zhe Song:
Fine-Grained Instance-Level Sketch-Based Video Retrieval. IEEE Trans. Circuits Syst. Video Technol. 31(5): 1995-2007 (2021) - [j29]Peng Xu, Yongye Huang, Tongtong Yuan, Tao Xiang, Timothy M. Hospedales, Yi-Zhe Song, Liang Wang:
On Learning Semantic Representations for Large-Scale Abstract Sketches. IEEE Trans. Circuits Syst. Video Technol. 31(9): 3366-3379 (2021) - [j28]Anran Qi, Yulia Gryaditskaya, Jifei Song, Yongxin Yang, Yonggang Qi, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Toward Fine-Grained Sketch-Based 3D Shape Retrieval. IEEE Trans. Image Process. 30: 8595-8606 (2021) - [c128]Tianyuan Yu, Yongxin Yang, Da Li, Timothy M. Hospedales, Tao Xiang:
Simple and Effective Stochastic Neural Networks. AAAI 2021: 3252-3260 - [c127]Efthymia Tsamoura, Timothy M. Hospedales, Loizos Michael:
Neural-Symbolic Integration: A Compositional Perspective. AAAI 2021: 5051-5060 - [c126]Chenyang Zhao, Timothy M. Hospedales:
Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation. ACML 2021: 1237-1252 - [c125]Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya, Yannis Panagakis, Timothy M. Hospedales, Georgios Tzimiropoulos, Nicholas D. Lane, Maja Pantic:
Defensive Tensorization. BMVC 2021: 131 - [c124]Yuting Qiang, Yongxin Yang, Xueting Zhang, Yanwen Guo, Timothy M. Hospedales:
Tensor Composition Net for Visual Relationship Prediction. BMVC 2021: 434 - [c123]Miguel Jaques, Michael Burke, Timothy M. Hospedales:
NewtonianVAE: Proportional Control and Goal Identification From Pixels via Physical Latent Spaces. CVPR 2021: 4454-4463 - [c122]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
How Well Do Self-Supervised Models Transfer? CVPR 2021: 5414-5423 - [c121]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. CVPR 2021: 5672-5681 - [c120]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Cloud2Curve: Generation and Vectorization of Parametric Sketches. CVPR 2021: 7088-7097 - [c119]Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales:
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. ICCV 2021: 631-640 - [c118]Boyan Gao, Henry Gouk, Timothy M. Hospedales:
Searching for Robustness: Loss Learning for Noisy Classification Tasks. ICCV 2021: 6650-6659 - [c117]Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, Timothy M. Hospedales:
A Simple Feature Augmentation for Domain Generalization. ICCV 2021: 8866-8875 - [c116]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
Interpreting Knowledge Graph Relation Representation from Word Embeddings. ICLR 2021 - [c115]Henry Gouk, Timothy M. Hospedales, Massimiliano Pontil:
Distance-Based Regularisation of Deep Networks for Fine-Tuning. ICLR 2021 - [c114]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Weight-covariance alignment for adversarially robust neural networks. ICML 2021: 3047-3056 - [c113]Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy M. Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. NeurIPS (Competition and Demos) 2021: 80-96 - [c112]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. NeurIPS 2021: 22234-22246 - [c111]Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales:
A Channel Coding Benchmark for Meta-Learning. NeurIPS Datasets and Benchmarks 2021 - [i108]Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales:
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. CoRR abs/2101.02833 (2021) - [i107]Yiying Li, Wei Zhou, Huaimin Wang, Haibo Mi, Timothy M. Hospedales:
FedH2L: Federated Learning with Model and Statistical Heterogeneity. CoRR abs/2101.11296 (2021) - [i106]Boyan Gao, Henry Gouk, Timothy M. Hospedales:
Searching for Robustness: Loss Learning for Noisy Classification Tasks. CoRR abs/2103.00243 (2021) - [i105]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. CoRR abs/2103.13716 (2021) - [i104]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Cloud2Curve: Generation and Vectorization of Parametric Sketches. CoRR abs/2103.15536 (2021) - [i103]Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M. Hospedales, Yi-Zhe Song:
Towards Unsupervised Sketch-based Image Retrieval. CoRR abs/2105.08237 (2021) - [i102]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error. CoRR abs/2106.09613 (2021) - [i101]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. CoRR abs/2106.10575 (2021) - [i100]Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales:
A Channel Coding Benchmark for Meta-Learning. CoRR abs/2107.07579 (2021) - [i99]Miguel Jaques, Martin Asenov, Michael Burke, Timothy M. Hospedales:
Vision-based system identification and 3D keypoint discovery using dynamics constraints. CoRR abs/2109.05928 (2021) - [i98]Haebeom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy M. Hospedales, Sung Ju Hwang:
Online Hyperparameter Meta-Learning with Hypergradient Distillation. CoRR abs/2110.02508 (2021) - [i97]Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales:
Self-Supervised Representation Learning: Introduction, Advances and Challenges. CoRR abs/2110.09327 (2021) - [i96]Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya, Yannis Panagakis, Timothy M. Hospedales, Georgios Tzimiropoulos, Nicholas D. Lane, Maja Pantic:
Defensive Tensorization. CoRR abs/2110.13859 (2021) - [i95]Minyoung Kim, Timothy M. Hospedales:
Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation. CoRR abs/2111.05392 (2021) - [i94]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks. CoRR abs/2111.11398 (2021) - 2020
- [j27]Ling Shao, Hubert P. H. Shum, Timothy M. Hospedales:
Editorial: Special Issue on Machine Vision with Deep Learning. Int. J. Comput. Vis. 128(4): 771-772 (2020) - [j26]Feng Liu, Tao Xiang, Timothy M. Hospedales, Wankou Yang, Changyin Sun:
Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool. IEEE Trans. Pattern Anal. Mach. Intell. 42(2): 460-474 (2020) - [j25]Zhong Ji, Biying Cui, Huihui Li, Yu-Gang Jiang, Tao Xiang, Timothy M. Hospedales, Yanwei Fu:
Deep Ranking for Image Zero-Shot Multi-Label Classification. IEEE Trans. Image Process. 29: 6549-6560 (2020) - [j24]Conghui Hu, Da Li, Yongxin Yang, Timothy M. Hospedales, Yi-Zhe Song:
Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation. IEEE Trans. Image Process. 29: 9470-9481 (2020) - [j23]Ayan Kumar Bhunia, Ayan Das, Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yulia Gryaditskaya, Yi-Zhe Song:
Pixelor: a competitive sketching AI agent. so you think you can sketch? ACM Trans. Graph. 39(6): 166:1-166:15 (2020) - [c110]Yu Zheng, Bowei Chen, Timothy M. Hospedales, Yongxin Yang:
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach. AAAI 2020: 1242-1249 - [c109]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Deep Domain-Adversarial Image Generation for Domain Generalisation. AAAI 2020: 13025-13032 - [c108]Shreyank N. Gowda, Panagiotis Eustratiadis, Timothy M. Hospedales, Laura Sevilla-Lara:
ALBA: Reinforcement Learning for Video Object Segmentation. BMVC 2020 - [c107]Mustafa Taha Koçyigit, Laura Sevilla-Lara, Timothy M. Hospedales, Hakan Bilen:
Unsupervised Batch Normalization. CVPR Workshops 2020: 3994-3999 - [c106]Jean Kossaifi, Antoine Toisoul, Adrian Bulat, Yannis Panagakis, Timothy M. Hospedales, Maja Pantic:
Factorized Higher-Order CNNs With an Application to Spatio-Temporal Emotion Estimation. CVPR 2020: 6059-6068 - [c105]Ayan Kumar Bhunia, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval. CVPR 2020: 9776-9785 - [c104]Kaiyue Pang, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval. CVPR 2020: 10344-10352 - [c103]Juan-Manuel Pérez-Rúa, Xiatian Zhu, Timothy M. Hospedales, Tao Xiang:
Incremental Few-Shot Object Detection. CVPR 2020: 13843-13852 - [c102]Xiao Gong, Guosheng Hu, Timothy M. Hospedales, Yongxin Yang:
Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification. ECCV Workshops (1) 2020: 135-151 - [c101]Da Li, Timothy M. Hospedales:
Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation. ECCV (16) 2020: 382-403 - [c100]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Learning to Generate Novel Domains for Domain Generalization. ECCV (16) 2020: 561-578 - [c99]Yonggang Li, Guosheng Hu, Yongtao Wang, Timothy M. Hospedales, Neil Martin Robertson, Yongxin Yang:
Differentiable Automatic Data Augmentation. ECCV (22) 2020: 580-595 - [c98]