| Learning video object segmentation with visual memory P Tokmakov, K Alahari, C Schmid Proceedings of the IEEE International Conference on Computer Vision, 4481-4490, 2017 | 262 | 2017 |
| Learning motion patterns in videos P Tokmakov, K Alahari, C Schmid Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 227 | 2017 |
| Weakly-supervised semantic segmentation using motion cues P Tokmakov, K Alahari, C Schmid European Conference on Computer Vision, 388-404, 2016 | 66* | 2016 |
| One click mining: Interactive local pattern discovery through implicit preference and performance learning M Boley, M Mampaey, B Kang, P Tokmakov, S Wrobel Proceedings of the ACM SIGKDD workshop on interactive data exploration and …, 2013 | 66 | 2013 |
| Learning to segment moving objects P Tokmakov, C Schmid, K Alahari International Journal of Computer Vision 127 (3), 282-301, 2019 | 58 | 2019 |
| Learning compositional representations for few-shot recognition P Tokmakov, YX Wang, M Hebert Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 58 | 2019 |
| A structured model for action detection Y Zhang, P Tokmakov, M Hebert, C Schmid Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 53 | 2019 |
| Towards segmenting anything that moves A Dave, P Tokmakov, D Ramanan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 40 | 2019 |
| Tao: A large-scale benchmark for tracking any object A Dave, T Khurana, P Tokmakov, C Schmid, D Ramanan European conference on computer vision, 436-454, 2020 | 31 | 2020 |
| Relational linear programming K Kersting, M Mladenov, P Tokmakov Artificial Intelligence 244, 188-216, 2017 | 26* | 2017 |
| Unsupervised learning of video representations via dense trajectory clustering P Tokmakov, M Hebert, C Schmid European Conference on Computer Vision, 404-421, 2020 | 11 | 2020 |
| A study on action detection in the wild Y Zhang, P Tokmakov, M Hebert, C Schmid arXiv preprint arXiv:1904.12993, 2019 | 9 | 2019 |
| Learning to Track with Object Permanence P Tokmakov, J Li, W Burgard, A Gaidon arXiv preprint arXiv:2103.14258, 2021 | 8 | 2021 |
| Learning to track any object A Dave, P Tokmakov, C Schmid, D Ramanan arXiv preprint arXiv:1910.11844, 2019 | 4 | 2019 |
| Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty B Ivanovic, KH Lee, P Tokmakov, B Wulfe, R McAllister, A Gaidon, ... arXiv preprint arXiv:2104.12446, 2021 | 3 | 2021 |
| Towards latent attribute discovery from triplet similarities I Nigam, P Tokmakov, D Ramanan Proceedings of the IEEE/CVF International Conference on Computer Vision, 402-410, 2019 | 1 | 2019 |
| Unlocking the Full Potential of Small Data with Diverse Supervision Z Pang, Z Hu, P Tokmakov, YX Wang, M Hebert Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | | 2021 |
| Learning Generalizable Representations via Diverse Supervision Z Pang, Z Hu, P Tokmakov, YX Wang, M Hebert arXiv e-prints, arXiv: 1911.12911, 2019 | | 2019 |
| Self-Supervised Robot Learning DP Gandhi Carnegie Mellon University Pittsburgh, PA, 2019 | | 2019 |
| Learning from motion P Tokmakov Université Grenoble Alpes, 2018 | | 2018 |
