Megadepth: Learning single-view depth prediction from internet photos Z Li, N Snavely Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1042 | 2018 |
Neural scene flow fields for space-time view synthesis of dynamic scenes Z Li, S Niklaus, N Snavely, O Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 623 | 2021 |
Learning the depths of moving people by watching frozen people Z Li, T Dekel, F Cole, R Tucker, N Snavely, C Liu, WT Freeman Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 257 | 2019 |
Learning intrinsic image decomposition from watching the world Z Li, N Snavely Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 174 | 2018 |
Cgintrinsics: Better intrinsic image decomposition through physically-based rendering Z Li, N Snavely Proceedings of the European conference on computer vision (ECCV), 371-387, 2018 | 159 | 2018 |
Dynibar: Neural dynamic image-based rendering Z Li, Q Wang, F Cole, R Tucker, N Snavely Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 122 | 2023 |
Neural 3d reconstruction in the wild J Sun, X Chen, Q Wang, Z Li, H Averbuch-Elor, X Zhou, N Snavely ACM SIGGRAPH 2022 conference proceedings, 1-9, 2022 | 87 | 2022 |
Iron: Inverse rendering by optimizing neural sdfs and materials from photometric images K Zhang, F Luan, Z Li, N Snavely Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 80 | 2022 |
Tracking everything everywhere all at once Q Wang, YY Chang, R Cai, Z Li, B Hariharan, A Holynski, N Snavely Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 69 | 2023 |
Crowdsampling the plenoptic function Z Li, W Xian, A Davis, N Snavely Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 69 | 2020 |
Large scale image mosaic construction for agricultural applications Z Li, V Isler IEEE Robotics and Automation Letters 1 (1), 295-302, 2016 | 56 | 2016 |
Deformable sprites for unsupervised video decomposition V Ye, Z Li, R Tucker, A Kanazawa, N Snavely Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 49 | 2022 |
Infinitenature-zero: Learning perpetual view generation of natural scenes from single images Z Li, Q Wang, N Snavely, A Kanazawa European Conference on Computer Vision, 515-534, 2022 | 43 | 2022 |
UprightNet: geometry-aware camera orientation estimation from single images W Xian, Z Li, M Fisher, J Eisenmann, E Shechtman, N Snavely Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 41 | 2019 |
Generative image dynamics Z Li, R Tucker, N Snavely, A Holynski Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 29 | 2024 |
MannequinChallenge: Learning the depths of moving people by watching frozen people Z Li, T Dekel, F Cole, R Tucker, N Snavely, C Liu, WT Freeman IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (12), 4229 …, 2020 | 20 | 2020 |
Persistent nature: A generative model of unbounded 3d worlds L Chai, R Tucker, Z Li, P Isola, N Snavely Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 16 | 2023 |
Structure and motion from casual videos Z Zhang, F Cole, Z Li, M Rubinstein, N Snavely, WT Freeman European Conference on Computer Vision, 20-37, 2022 | 14 | 2022 |
3d moments from near-duplicate photos Q Wang, Z Li, D Salesin, N Snavely, B Curless, J Kontkanen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 12 | 2022 |
Depth determination for images captured with a moving camera and representing moving features T Dekel, C Forrester, C Liu, W Freeman, R Tucker, N Snavely, Z Li US Patent 11,315,274, 2022 | 8 | 2022 |