| Synthetic Data for Text Localisation in Natural Images A Gupta, A Vedaldi, A Zisserman IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 | 1866 | 2016 |
| VGG image annotator (VIA) A Dutta, A Gupta, A Zissermann URL: http://www.robots.ox.ac.uk/~vgg/software/via, 2016 | 463* | 2016 |
| CrossTransformers: spatially-aware few-shot transfer C Doersch, A Gupta, A Zisserman Neural Information Processing Systems (NeurIPS), 2020 | 394 | 2020 |
| Unsupervised learning of object landmarks through conditional image generation T Jakab, A Gupta, H Bilen, A Vedaldi Neural Information Processing Systems (NeurIPS), 4016-4027, 2018 | 306 | 2018 |
| Unsupervised learning of object keypoints for perception and control TD Kulkarni, A Gupta, C Ionescu, S Borgeaud, M Reynolds, A Zisserman, ... Neural Information Processing Systems (NeurIPS), 10723-10733, 2019 | 225 | 2019 |
| TAP-Vid: A Benchmark for Tracking Any Point in a Video C Doersch, A Gupta, L Markeeva, AR Continente, L Smaira, Y Aytar, ... Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2022 | 145 | 2022 |
| TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement C Doersch, Y Yang, M Vecerik, D Gokay, A Gupta, Y Aytar, J Carreira, ... International Conference on Computer Vision (ICCV), 2023 | 129 | 2023 |
| A case study of trajectory transfer through non-rigid registration for a simplified suturing scenario J Schulman, A Gupta, S Venkatesan, M Tayson-Frederick, P Abbeel International Conference on Intelligent Robots and Systems (IROS), 4111-4117, 2013 | 123 | 2013 |
| Self-supervised Learning of Interpretable Keypoints from Unlabelled Videos T Jakab, A Gupta, H Bilen, A Vedaldi IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 108* | 2020 |
| Temporal Query Networks for Fine-grained Video Understanding C Zhang, A Gupta, A Zisserman IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 105 | 2021 |
| Sus-x: Training-free name-only transfer of vision-language models V Udandarao, A Gupta, S Albanie International Conference on Computer Vision (ICCV), 2023 | 99 | 2023 |
| Perception Test: A Diagnostic Benchmark for Multimodal Video Models V Pătrăucean, L Smaira, A Gupta, AR Continente, L Markeeva, D Banarse, ... Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2023 | 94* | 2023 |
| Adaptive Text Recognition through Visual Matching C Zhang, A Gupta, A Zisserman European Conference on Computer Vision (ECCV), 2020 | 41 | 2020 |
| Is an Object-Centric Video Representation Beneficial for Transfer? C Zhang, A Gupta, A Zisserman Asian Conference on Computer Vision (ACCV), 1976-1994, 2022 | 28 | 2022 |
| Learning to read by spelling: Towards unsupervised text recognition A Gupta, A Vedaldi, A Zisserman Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP …, 2018 | 26 | 2018 |
| Bootstap: Bootstrapped training for tracking-any-point C Doersch, P Luc, Y Yang, D Gokay, S Koppula, A Gupta, J Heyward, ... Proceedings of the Asian Conference on Computer Vision, 3257-3274, 2024 | 17 | 2024 |
| Helping Hands: An Object-Aware Ego-Centric Video Recognition Model C Zhang, A Gupta, A Zisserman International Conference on Computer Vision (ICCV), 2023 | 17 | 2023 |
| Representation Matters: Improving Perception and Exploration for Robotics M Wulfmeier, A Byravan, T Hertweck, I Higgins, A Gupta, T Kulkarni, ... IEEE International Conference on Robotics and Automation (ICRA), 2020 | 17 | 2020 |
| Inductive Visual Localisation: Factorised Training for Superior Generalisation A Gupta, A Vedaldi, A Zisserman British Machine Vision Conference (BMVC) 2018, 2018 | 7 | 2018 |
| Veo: our most capable generative video model. 2024 G Deepmind URL https://deepmind. google/technologies/veo, 0 | 2 | |
Andrew ZissermanUniversity of OxfordE-mail megerősítve itt: robots.ox.ac.uk