| Megadepth: Learning single-view depth prediction from internet photos Z Li, N Snavely Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 466 | 2018 |
| 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 | 148 | 2019 |
| 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 | 119 | 2021 |
| Learning intrinsic image decomposition from watching the world Z Li, N Snavely Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 102 | 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 | 89 | 2018 |
| Large scale image mosaic construction for agricultural applications Z Li, V Isler IEEE Robotics and Automation Letters 1 (1), 295-302, 2016 | 45 | 2016 |
| Crowdsampling the plenoptic function Z Li, W Xian, A Davis, N Snavely European Conference on Computer Vision, 178-196, 2020 | 28 | 2020 |
| 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 | 20 | 2019 |
| 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 | 4 | 2020 |
| 3D Moments from Near-Duplicate Photos Q Wang, Z Li, D Salesin, N Snavely, B Curless, J Kontkanen arXiv preprint arXiv:2205.06255, 2022 | | 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 | | 2022 |
| Deformable Sprites for Unsupervised Video Decomposition V Ye, Z Li, R Tucker, A Kanazawa, N Snavely arXiv preprint arXiv:2204.07151, 2022 | | 2022 |
| IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images K Zhang, F Luan, Z Li, N Snavely arXiv preprint arXiv:2204.02232, 2022 | | 2022 |
| Large scale image mosaic construction for agricultural applications IV Isler, Z Li US Patent 10,453,178, 2019 | | 2019 |
| Supplementary Materials for IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images K Zhang, F Luan, Z Li, N Snavely | | |
| Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes Supplementary Material Z Li, S Niklaus, N Snavely, O Wang, C Tech | | |
| Supplementary Material Learning the Depths of Moving People by Watching Frozen People Z Li, T Dekel, F Cole, R Tucker, N Snavely, C Liu, WT Freeman | | |
| High-Speed Autonomous Quadrotor Navigation through Image Paths T Do, LC Carrillo-Arce, Z Li, SI Roumeliotis | | |
| UprightNet: Geometry-Aware Camera Orientation Estimation from Single Images Supplementary Material W Xian, Z Li, MFJEE Shechtman, N Snavely | | |
| Supplementary Material: CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering Z Li, N Snavely | | |
Noah SnavelyAssociate Professor, Cornell University and Researcher at Google ResearchVerified email at cs.cornell.edu
