| Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling J Wu, C Zhang, T Xue, WT Freeman, JB Tenenbaum Advances In Neural Information Processing Systems, 82-90, 2016 | 1307 | 2016 |
| Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks T Xue, J Wu, KL Bouman, WT Freeman Advances in neural information processing systems, 91-99, 2016 | 407 | 2016 |
| Deep Multiple Instance Learning for Image Classification and Auto-Annotation J Wu, Y Yu, C Huang, K Yu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 3460-3469, 2015 | 372 | 2015 |
| Video Enhancement with Task-Oriented Flow T Xue, B Chen, J Wu, D Wei, WT Freeman International Journal of Computer Vision 127 (8), 1106-1125, 2019 | 365 | 2019 |
| Single Image 3D Interpreter Network J Wu, T Xue, JJ Lim, Y Tian, JB Tenenbaum, A Torralba, WT Freeman European Conference on Computer Vision, 365-382, 2016 | 326 | 2016 |
| Ambient Sound Provides Supervision for Visual Learning A Owens, J Wu, JH McDermott, WT Freeman, A Torralba European Conference on Computer Vision, 801-816, 2016 | 317 | 2016 |
| MarrNet: 3D Shape Reconstruction via 2.5D Sketches J Wu, Y Wang, T Xue, X Sun, WT Freeman, JB Tenenbaum Advances in Neural Information Processing Systems, 540-550, 2017 | 295 | 2017 |
| Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning J Wu, I Yildirim, JJ Lim, WT Freeman, JB Tenenbaum Advances in Neural Information Processing Systems, 127-135, 2015 | 288 | 2015 |
| The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences from Natural Supervision J Mao, C Gan, P Kohli, JB Tenenbaum, J Wu International Conference on Learning Representations, 2019 | 287 | 2019 |
| Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding K Yi, J Wu, C Gan, A Torralba, P Kohli, JB Tenenbaum Advances in Neural Information Processing Systems, 1031-1042, 2018 | 268 | 2018 |
| 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 | 202 | 2018 |
| Harvesting Mid-Level Visual Concepts from Large-Scale Internet Images Q Li, J Wu, Z Tu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 851-858, 2013 | 170 | 2013 |
| Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks A Arsalan Soltani, H Huang, J Wu, TD Kulkarni, JB Tenenbaum Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 168 | 2017 |
| Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification X Long, C Gan, G de Melo, J Wu, X Liu, S Wen Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 166 | 2018 |
| Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning JY Zhu, J Wu, Y Xu, E Chang, Z Tu IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (4), 862-875, 2015 | 144 | 2015 |
| Learning to See Physics via Visual De-animation J Wu, E Lu, P Kohli, WT Freeman, JB Tenenbaum Advances in Neural Information Processing Systems, 153-164, 2017 | 140 | 2017 |
| 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 | 115* | 2018 |
| CLEVRER: CoLlision Events for Video REpresentation and Reasoning K Yi, C Gan, Y Li, P Kohli, J Wu, A Torralba, JB Tenenbaum arXiv preprint arXiv:1910.01442, 2019 | 113 | 2019 |
| Neural Scene De-rendering J Wu, JB Tenenbaum, P Kohli Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 112 | 2017 |
| Raster-to-Vector: Revisiting Floorplan Transformation C Liu, J Wu, P Kohli, Y Furukawa Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 110 | 2017 |
Joshua B. TenenbaumMITVerified email at mit.edu
