| Unflow: Unsupervised learning of optical flow with a bidirectional census loss S Meister, J Hur, S Roth Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 666 | 2018 |
| Iterative residual refinement for joint optical flow and occlusion estimation J Hur, S Roth Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 353 | 2019 |
| Lumiere: A space-time diffusion model for video generation O Bar-Tal, H Chefer, O Tov, C Herrmann, R Paiss, S Zada, A Ephrat, J Hur, ... SIGGRAPH Asia 2024 Conference Papers, 1-11, 2024 | 215 | 2024 |
| Multi-lane detection in urban driving environments using conditional random fields J Hur, SN Kang, SW Seo 2013 IEEE Intelligent vehicles symposium (IV), 1297-1302, 2013 | 163 | 2013 |
| A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence J Zhang, C Herrmann, J Hur, L Polania Cabrera, V Jampani, D Sun, ... Advances in Neural Information Processing Systems 36, 45533-45547, 2023 | 144 | 2023 |
| Self-supervised monocular scene flow estimation J Hur, S Roth Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 129 | 2020 |
| Mirrorflow: Exploiting symmetries in joint optical flow and occlusion estimation J Hur, S Roth Proceedings of the IEEE International Conference on Computer Vision, 312-321, 2017 | 109 | 2017 |
| Joint optical flow and temporally consistent semantic segmentation J Hur, S Roth European Conference on Computer Vision Workshops, 163-177, 2016 | 90 | 2016 |
| The surprising effectiveness of diffusion models for optical flow and monocular depth estimation S Saxena, C Herrmann, J Hur, A Kar, M Norouzi, D Sun, DJ Fleet Advances in Neural Information Processing Systems 36, 39443-39469, 2023 | 84 | 2023 |
| Optical flow estimation in the deep learning age J Hur, S Roth Modelling human motion: from human perception to robot design, 119-140, 2020 | 69 | 2020 |
| Self-supervised multi-frame monocular scene flow J Hur, S Roth Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 65 | 2021 |
| Multi-lane detection based on accurate geometric lane estimation in highway scenarios SN Kang, S Lee, J Hur, SW Seo 2014 IEEE Intelligent Vehicles Symposium Proceedings, 221-226, 2014 | 63 | 2014 |
| Generalized deformable spatial pyramid: Geometry-preserving dense correspondence estimation J Hur, H Lim, C Park, S Chul Ahn Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 61 | 2015 |
| Monst3r: A simple approach for estimating geometry in the presence of motion J Zhang, C Herrmann, J Hur, V Jampani, T Darrell, F Cole, D Sun, ... arXiv preprint arXiv:2410.03825, 2024 | 37 | 2024 |
| Wonderjourney: Going from anywhere to everywhere HX Yu, H Duan, J Hur, K Sargent, M Rubinstein, WT Freeman, F Cole, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 36 | 2024 |
| Telling left from right: Identifying geometry-aware semantic correspondence J Zhang, C Herrmann, J Hur, E Chen, V Jampani, D Sun, MH Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 27 | 2024 |
| Zero-shot metric depth with a field-of-view conditioned diffusion model S Saxena, J Hur, C Herrmann, D Sun, DJ Fleet arXiv preprint arXiv:2312.13252, 2023 | 14 | 2023 |
| RAFT-MSF: Self-supervised monocular scene flow using recurrent optimizer B Bayramli, J Hur, H Lu International Journal of Computer Vision 131 (11), 2757-2769, 2023 | 14 | 2023 |
| Self-supervised surround-view depth estimation with volumetric feature fusion JH Kim, J Hur, TP Nguyen, SG Jeong Advances in Neural Information Processing Systems 35, 4032-4045, 2022 | 13 | 2022 |
| Self-supervised autoflow HP Huang, C Herrmann, J Hur, E Lu, K Sargent, A Stone, MH Yang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
Deqing SunResearch Scientist, Google DeepMindBestätigte E-Mail-Adresse bei google.com
