| Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling J Wu, C Zhang, T Xue, WT Freeman, JB Tenenbaum arXiv preprint arXiv:1610.07584, 2016 | 1078 | 2016 |
| Pix3d: Dataset and methods for single-image 3d shape modeling X Sun, J Wu, X Zhang, Z Zhang, C Zhang, T Xue, JB Tenenbaum, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 143 | 2018 |
| Visual object networks: Image generation with disentangled 3d representation JY Zhu, Z Zhang, C Zhang, J Wu, A Torralba, JB Tenenbaum, ... arXiv preprint arXiv:1812.02725, 2018 | 74 | 2018 |
| Learning shape priors for single-view 3d completion and reconstruction J Wu, C Zhang, X Zhang, Z Zhang, WT Freeman, JB Tenenbaum Proceedings of the European Conference on Computer Vision (ECCV), 646-662, 2018 | 71 | 2018 |
| Learning to reconstruct shapes from unseen classes X Zhang, Z Zhang, C Zhang, JB Tenenbaum, WT Freeman, J Wu arXiv preprint arXiv:1812.11166, 2018 | 66 | 2018 |
| A comparative evaluation of approximate probabilistic simulation and deep neural networks as accounts of human physical scene understanding R Zhang, J Wu, C Zhang, WT Freeman, JB Tenenbaum arXiv preprint arXiv:1605.01138, 2016 | 29 | 2016 |
| Seeing tree structure from vibration T Xue, J Wu, Z Zhang, C Zhang, JB Tenenbaum, WT Freeman Proceedings of the European Conference on Computer Vision (ECCV), 748-764, 2018 | 5 | 2018 |
| Generative adversarial modeling of 3D shapes C Zhang Massachusetts Institute of Technology, 2018 | 1 | 2018 |
Jiajun WuStanford UniversityVerified email at cs.stanford.edu
