| Learning latent dynamics for planning from pixels D Hafner, T Lillicrap, I Fischer, R Villegas, D Ha, H Lee, J Davidson Proceedings of the 36th International Conference on Machine Learning, 2019 | 1652 | 2019 |
| Decomposing motion and content for natural video sequence prediction R Villegas, J Yang, S Hong, X Lin, H Lee International Conference on Learning Representations, 2017 | 708 | 2017 |
| Learning to generate long-term future via hierarchical prediction R Villegas, J Yang, Y Zou, S Sohn, X Lin, H Lee Proceedings of the 34th International Conference on Machine Learning, 2017 | 445 | 2017 |
| Phenaki: Variable length video generation from open domain textual descriptions R Villegas, M Babaeizadeh, PJ Kindermans, H Moraldo, H Zhang, ... International Conference on Learning Representations, 2022 | 343 | 2022 |
| Improving object detection with deep convolutional networks via bayesian optimization and structured prediction Y Zhang, K Sohn, R Villegas, G Pan, H Lee Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 279 | 2015 |
| Neural Kinematic Networks for Unsupervised Motion Retargetting R Villegas, J Yang, D Ceylan, H Lee Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 251 | 2018 |
| MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics X Yan, A Rastogi, R Villegas, K Sunkavalli, E Shechtman, S Hadap, ... European Conference on Computer Vision (ECCV), 2018, 2018 | 168 | 2018 |
| Unsupervised learning of object structure and dynamics from videos M Minderer, C Sun, R Villegas, F Cole, KP Murphy, H Lee Advances in Neural Information Processing Systems 32, 2019 | 163 | 2019 |
| Hierarchical Long-term Video Prediction without Supervision N Wichers, R Villegas, D Erhan, H Lee Proceedings of the 35th International Conference on Machine Learning, 2018 | 162 | 2018 |
| High fidelity video prediction with large stochastic recurrent neural networks R Villegas, A Pathak, H Kannan, D Erhan, QV Le, H Lee Advances in Neural Information Processing Systems 32, 2019 | 156 | 2019 |
| Stochastic scene-aware motion prediction M Hassan, D Ceylan, R Villegas, J Saito, J Yang, Y Zhou, MJ Black Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 153 | 2021 |
| Who do i look like? determining parent-offspring resemblance via gated autoencoders A Dehghan, EG Ortiz, R Villegas, M Shah Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 144 | 2014 |
| Contact and human dynamics from monocular video D Rempe, LJ Guibas, A Hertzmann, B Russell, R Villegas, J Yang Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 109 | 2020 |
| Future object trajectory predictions for autonomous machine applications R Villegas, A Troccoli, I Frosio, S Tyree, W Byeon, J Kautz US Patent 11,514,293, 2022 | 53 | 2022 |
| Task-generic hierarchical human motion prior using vaes J Li, R Villegas, D Ceylan, J Yang, Z Kuang, H Li, Y Zhao 2021 International Conference on 3D Vision (3DV), 771-781, 2021 | 48 | 2021 |
| Contact-aware retargeting of skinned motion R Villegas, D Ceylan, A Hertzmann, J Yang, J Saito Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 40 | 2021 |
| Single-image full-body human relighting M Lagunas, X Sun, J Yang, R Villegas, J Zhang, Z Shu, B Masia, ... arXiv preprint arXiv:2107.07259, 2021 | 34 | 2021 |
| Retargeting skeleton motion sequences through cycle consistency adversarial training of a motion synthesis neural network with a forward kinematics layer J Yang, D Ceylan, R Villegas US Patent 10,546,408, 2020 | 23 | 2020 |
| ViC-MAE: self-supervised representation learning from images and video with contrastive masked autoencoders J Hernandez, R Villegas, V Ordonez European Conference on Computer Vision, 444-463, 2025 | 7 | 2025 |
| Motion retargeting with kinematic constraints RE Villegas, J Saito, J Yang, DC Aksit US Patent 11,625,881, 2023 | 4 | 2023 |
Jimei YangSenior Research Scientist, Adobe ResearchEmail verificata su adobe.com
