| Distribution fields for tracking L Sevilla-Lara, EG Learned-Miller IEEE Conference on Computer Vision and Pattern Recognition, 2012 | 738 | 2012 |
| Adaptive prototype learning and allocation for few-shot segmentation G Li, V Jampani, L Sevilla-Lara, D Sun, J Kim, J Kim Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 446 | 2021 |
| On the integration of optical flow and action recognition L Sevilla-Lara, Y Liao, F Güney, V Jampani, A Geiger, MJ Black Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019 | 270 | 2019 |
| Optical flow with semantic segmentation and localized layers L Sevilla-Lara, D Sun, V Jampani, MJ Black Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 244 | 2016 |
| Smart frame selection for action recognition SN Gowda, M Rohrbach, L Sevilla-Lara Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1451-1459, 2021 | 190 | 2021 |
| Dmc-net: Generating discriminative motion cues for fast compressed video action recognition Z Shou, X Lin, Y Kalantidis, L Sevilla-Lara, M Rohrbach, SF Chang, Z Yan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 160 | 2019 |
| Optical flow in mostly rigid scenes J Wulff, L Sevilla-Lara, MJ Black Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 144 | 2017 |
| Only time can tell: Discovering temporal data for temporal modeling L Sevilla-Lara, S Zha, Z Yan, V Goswami, M Feiszli, L Torresani Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021 | 92 | 2021 |
| Faster recurrent networks for efficient video classification L Zhu, D Tran, L Sevilla-Lara, Y Yang, M Feiszli, H Wang Proceedings of the AAAI conference on artificial intelligence 34 (07), 13098 …, 2020 | 78 | 2020 |
| Learn2augment: learning to composite videos for data augmentation in action recognition SN Gowda, M Rohrbach, F Keller, L Sevilla-Lara European conference on computer vision, 242-259, 2022 | 43 | 2022 |
| Locate: Localize and transfer object parts for weakly supervised affordance grounding G Li, V Jampani, D Sun, L Sevilla-Lara Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 40 | 2023 |
| Optical flow estimation with channel constancy L Sevilla-Lara, D Sun, EG Learned-Miller, MJ Black Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 39 | 2014 |
| Claster: clustering with reinforcement learning for zero-shot action recognition SN Gowda, L Sevilla-Lara, F Keller, M Rohrbach European Conference on Computer Vision, 187-203, 2022 | 35 | 2022 |
| A new split for evaluating true zero-shot action recognition SN Gowda, L Sevilla-Lara, K Kim, F Keller, M Rohrbach DAGM German Conference on Pattern Recognition, 191-205, 2021 | 33 | 2021 |
| Alba: Reinforcement learning for video object segmentation SN Gowda, P Eustratiadis, T Hospedales, L Sevilla-Lara arXiv preprint arXiv:2005.13039, 2020 | 17 | 2020 |
| Watt for what: Rethinking deep learning's energy-performance relationship SN Gowda, X Hao, G Li, SN Gowda, X Jin, L Sevilla-Lara arXiv preprint arXiv:2310.06522, 2023 | 12 | 2023 |
| Automated looping video creation L Sevilla-Lara, E Shechtman, KK Sunkavalli US Patent 9,672,866, 2017 | 12 | 2017 |
| One-shot open affordance learning with foundation models G Li, D Sun, L Sevilla-Lara, V Jampani Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 11 | 2024 |
| " What Is Optical Flow for?": Workshop Results and Summary F Guney, L Sevilla-Lara, D Sun, J Wulff Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 9 | 2018 |
| Smooth loops from unconstrained video L Sevilla‐Lara, J Wulff, K Sunkavalli, E Shechtman Computer Graphics Forum 34 (4), 99-107, 2015 | 9 | 2015 |
Shreyank N GowdaAssistant Professor at the University of Nottinghamnottingham.ac.uk의 이메일 확인됨