| 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 | 217 | 2017 |
| Learning motion patterns in videos P Tokmakov, K Alahari, C Schmid Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 185 | 2017 |
| Weakly-supervised semantic segmentation using motion cues P Tokmakov, K Alahari, C Schmid European Conference on Computer Vision, 388-404, 2016 | 61* | 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 | 60 | 2013 |
| Learning to segment moving objects P Tokmakov, C Schmid, K Alahari International Journal of Computer Vision 127 (3), 282-301, 2019 | 44 | 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 | 44 | 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 | 34 | 2019 |
| Towards segmenting anything that moves A Dave, P Tokmakov, D Ramanan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 26 | 2019 |
| Relational linear programming K Kersting, M Mladenov, P Tokmakov Artificial Intelligence 244, 188-216, 2017 | 26* | 2017 |
| 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 | 14 | 2020 |
| A study on action detection in the wild Y Zhang, P Tokmakov, M Hebert, C Schmid arXiv preprint arXiv:1904.12993, 2019 | 7 | 2019 |
| Unsupervised learning of video representations via dense trajectory clustering P Tokmakov, M Hebert, C Schmid European Conference on Computer Vision, 404-421, 2020 | 4 | 2020 |
| Learning to track any object A Dave, P Tokmakov, C Schmid, D Ramanan arXiv preprint arXiv:1910.11844, 2019 | 3 | 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 | | 2021 |
| Learning to Track with Object Permanence P Tokmakov, J Li, W Burgard, A Gaidon arXiv preprint arXiv:2103.14258, 2021 | | 2021 |
| Context Aware Group Activity Recognition A Dasgupta, CV Jawahar, K Alahari 2020 25th International Conference on Pattern Recognition (ICPR), 10098-10105, 2021 | | 2021 |
| Learning Generalizable Representations via Diverse Supervision Z Pang, Z Hu, P Tokmakov, YX Wang, M Hebert arXiv preprint arXiv:1911.12911, 2019 | | 2019 |
| 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 | | 2019 |
| Learning from motion P Tokmakov Université Grenoble Alpes, 2018 | | 2018 |
| Implementation and integration of Exceptional Model Mining Framework into One Click Mining Project E Efendiev, M Boley, P Tokmakov | | 2014 |
