| Distribution fields for tracking L Sevilla-Lara, EG Learned-Miller IEEE Conference on Computer Vision and Pattern Recognition, 2012 | 663 | 2012 |
| Distribution fields for tracking L Sevilla-Lara, E Learned-Miller 2012 IEEE Conference on computer vision and pattern recognition, 1910-1917, 2012 | 624 | 2012 |
| 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 | 154 | 2016 |
| On the integration of optical flow and action recognition L Sevilla-Lara, Y Liao, F Güney, V Jampani, A Geiger, MJ Black German Conference on Pattern Recognition, 281-297, 2018 | 91 | 2018 |
| Optical flow in mostly rigid scenes J Wulff, L Sevilla-Lara, MJ Black Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 81 | 2017 |
| 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 | 37 | 2019 |
| Optical flow estimation with channel constancy L Sevilla-Lara, D Sun, EG Learned-Miller, MJ Black European Conference on Computer Vision, 423-438, 2014 | 36 | 2014 |
| 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 | 17 | 2020 |
| 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 | 10 | 2021 |
| Automated looping video creation L Sevilla-Lara, E Shechtman, KK Sunkavalli US Patent 9,672,866, 2017 | 9 | 2017 |
| Smooth loops from unconstrained video L SevillaLara, J Wulff, K Sunkavalli, E Shechtman Computer Graphics Forum 34 (4), 99-107, 2015 | 7 | 2015 |
| ALBA: Reinforcement Learning for Video Object Segmentation SN Gowda, P Eustratiadis, T Hospedales, L Sevilla-Lara arXiv preprint arXiv:2005.13039, 2020 | 4 | 2020 |
| Distribution Fields with Adaptive Kernels for Large Displacement Image Alignment B Mears, L Sevilla-Lara, E Learned-Miller BMVC 56 (3), 221-255, 2013 | 4* | 2013 |
| Distribution Fields L Sevilla-Lara, EG Learned-Miller UMass Amherst Technical Report, 2011 | 4 | 2011 |
| Distribution fields L Sevilla-Lara, E Learned-Miller Technical Report, University of Massachusetts Amherst, 2011 | 4 | 2011 |
| " 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 | 3 | 2018 |
| Unsupervised Batch Normalization MT Koçyigit, L Sevilla-Lara, TM Hospedales, H Bilen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 1 | 2020 |
| Adaptive Prototype Learning and Allocation for Few-Shot Segmentation G Li, V Jampani, L Sevilla-Lara, D Sun, J Kim, J Kim arXiv preprint arXiv:2104.01893, 2021 | | 2021 |
| CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition SN Gowda, L Sevilla-Lara, F Keller, M Rohrbach arXiv preprint arXiv:2101.07042, 2021 | | 2021 |
| SMART Frame Selection for Action Recognition SN Gowda, M Rohrbach, L Sevilla-Lara arXiv preprint arXiv:2012.10671, 2020 | | 2020 |
Erik Learned-MillerProfessor of Computer Science, University of Massachusetts Amherst在 cs.umass.edu 的电子邮件经过验证
