| Synthesizing training images for boosting human 3d pose estimation W Chen, H Wang, Y Li, H Su, Z Wang, C Tu, D Lischinski, D Cohen-Or, ... 2016 Fourth International Conference on 3D Vision (3DV), 479-488, 2016 | 293 | 2016 |
| Learning to predict 3d objects with an interpolation-based differentiable renderer W Chen, H Ling, J Gao, E Smith, J Lehtinen, A Jacobson, S Fidler Advances in neural information processing systems 32, 2019 | 250 | 2019 |
| Fast interactive object annotation with curve-gcn H Ling, J Gao, A Kar, W Chen, S Fidler Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 191 | 2019 |
| Image gans meet differentiable rendering for inverse graphics and interpretable 3d neural rendering Y Zhang, W Chen, H Ling, J Gao, Y Zhang, A Torralba, S Fidler arXiv preprint arXiv:2010.09125, 2020 | 77 | 2020 |
| Steady-state non-line-of-sight imaging W Chen, S Daneau, F Mannan, F Heide Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 47 | 2019 |
| Learning deformable tetrahedral meshes for 3d reconstruction J Gao, W Chen, T Xiang, A Jacobson, M McGuire, S Fidler Advances In Neural Information Processing Systems 33, 9936-9947, 2020 | 40 | 2020 |
| Kaolin: A pytorch library for accelerating 3d deep learning research KM Jatavallabhula, E Smith, JF Lafleche, CF Tsang, A Rozantsev, ... arXiv preprint arXiv:1911.05063, 2019 | 40 | 2019 |
| Learned feature embeddings for non-line-of-sight imaging and recognition W Chen, F Wei, KN Kutulakos, S Rusinkiewicz, F Heide ACM Transactions on Graphics (ToG) 39 (6), 1-18, 2020 | 38 | 2020 |
| Extracting triangular 3d models, materials, and lighting from images J Munkberg, J Hasselgren, T Shen, J Gao, W Chen, A Evans, T Müller, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 36 | 2022 |
| Optimal structured light a la carte P Mirdehghan, W Chen, KN Kutulakos Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 30 | 2018 |
| 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, 2022 | 25 | 2022 |
| Hallucinating stereoscopy from a single image Q Zeng, W Chen, H Wang, C Tu, D Cohen‐Or, D Lischinski, B Chen Computer Graphics Forum 34 (2), 1-12, 2015 | 19 | 2015 |
| Kaolin: A pytorch library for accelerating 3d deep learning research J Krishna Murthy, E Smith, JF Lafleche, CF Tsang, A Rozantsev, W Chen, ... arXiv preprint arXiv:1911.05063 1, 2019 | 16 | 2019 |
| 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 | 14 | 2021 |
| Auto-tuning structured light by optical stochastic gradient descent W Chen, P Mirdehghan, S Fidler, KN Kutulakos Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 10 | 2020 |
| Kaolin: A PyTorch library for accelerating 3d deep learning research ES KJ, JF Lafleche, CF Tsang, A Rozantsev, W Chen, T Xiang, ... arXiv preprint arXiv:1911.05063 2, 2019 | 8 | 2019 |
| Generating labels for synthetic images using one or more neural networks Y Zhang, H Ling, J Gao, W Chen, AT Barriuso, S Fidler US Patent App. 17/020,649, 2022 | 5 | 2022 |
| Systems and methods for polygon object annotation and a method of training and object annotation system S Fidler, A Kar, H Ling, J Gao, W Chen, DJA Marrero US Patent 10,643,130, 2020 | 5 | 2020 |
| A holistic approach for data-driven object cutout H Xu, Y Li, W Chen, D Lischinski, D Cohen-Or, B Chen Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 4 | 2017 |
| Neural Light Field Estimation for Street Scenes with Differentiable Virtual Object Insertion Z Wang, W Chen, D Acuna, J Kautz, S Fidler Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 1 | 2022 |
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
