| Get3d: A generative model of high quality 3d textured shapes learned from images J Gao, T Shen, Z Wang, W Chen, K Yin, D Li, O Litany, Z Gojcic, S Fidler Advances In Neural Information Processing Systems 35, 31841-31854, 2022 | 422 | 2022 |
| Object instance annotation with deep extreme level set evolution Z Wang, D Acuna, H Ling, A Kar, S Fidler Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 90 | 2019 |
| Flexible Isosurface Extraction for Gradient-Based Mesh Optimization. T Shen, J Munkberg, J Hasselgren, K Yin, Z Wang, W Chen, Z Gojcic, ... ACM Trans. Graph. 42 (4), 37:1-37:16, 2023 | 72 | 2023 |
| Learning indoor inverse rendering with 3d spatially-varying lighting Z Wang, J Philion, S Fidler, J Kautz Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 72 | 2021 |
| Multi-stream deep neural networks for rgb-d egocentric action recognition Y Tang, Z Wang, J Lu, J Feng, J Zhou IEEE Transactions on Circuits and Systems for Video Technology 29 (10), 3001 …, 2018 | 70 | 2018 |
| Neural fields meet explicit geometric representations for inverse rendering of urban scenes Z Wang, T Shen, J Gao, S Huang, J Munkberg, J Hasselgren, Z Gojcic, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 68 | 2023 |
| DIB-R++: learning to predict lighting and material with a hybrid differentiable renderer W Chen, J Litalien, J Gao, Z Wang, C Fuji Tsang, S Khamis, O Litany, ... Advances in Neural Information Processing Systems 34, 22834-22848, 2021 | 62 | 2021 |
| Learning semantics-preserving attention and contextual interaction for group activity recognition Y Tang, J Lu, Z Wang, M Yang, J Zhou IEEE Transactions on Image Processing 28 (10), 4997-5012, 2019 | 55 | 2019 |
| Mining semantics-preserving attention for group activity recognition Y Tang, Z Wang, P Li, J Lu, M Yang, J Zhou Proceedings of the 26th ACM international conference on Multimedia, 1283-1291, 2018 | 53 | 2018 |
| Adaptive shells for efficient neural radiance field rendering Z Wang, T Shen, M Nimier-David, N Sharp, J Gao, A Keller, S Fidler, ... arXiv preprint arXiv:2311.10091, 2023 | 47 | 2023 |
| Neural lidar fields for novel view synthesis S Huang, Z Gojcic, Z Wang, F Williams, Y Kasten, S Fidler, K Schindler, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 44 | 2023 |
| Neural light field estimation for street scenes with differentiable virtual object insertion Z Wang, W Chen, D Acuna, J Kautz, S Fidler European Conference on Computer Vision, 380-397, 2022 | 33 | 2022 |
| Beyond fixed grid: Learning geometric image representation with a deformable grid J Gao, Z Wang, J Xuan, S Fidler Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 26 | 2020 |
| Toronto annotation suite A Kar, SW Kim, M Boben, J Gao, T Li, H Ling, Z Wang, S Fidler | 10 | 2021 |
| Photorealistic object insertion with diffusion-guided inverse rendering R Liang, Z Gojcic, M Nimier-David, D Acuna, N Vijaykumar, S Fidler, ... European Conference on Computer Vision, 446-465, 2025 | 1 | 2025 |
| Hybrid differentiable rendering for light transport simulation systems and applications W Chen, J Litalien, J Gao, Z Wang, CTTCL Fuji, S Khamis, O Litany, ... US Patent 11,922,558, 2024 | 1 | 2024 |
| Supplementary Material: Neural Fields meet Explicit Geometric Representations for Inverse Rendering of Urban Scenes Z Wang, T Shen, J Gao, S Huang, J Munkberg, J Hasselgren, Z Gojcic, ... | | |
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
