| Neural Volumes: Learning Dynamic Renderable Volumes from Images S Lombardi, T Simon, J Saragih, G Schwartz, AM Lehrmann, Y Sheikh Transactions on Graphics (TOG), 2019 | 189 | 2019 |
| Efficient Nonlinear Markov Models for Human Motion AM Lehrmann, PV Gehler, S Nowozin Computer Vision and Pattern Recognition (CVPR), 2014 | 106 | 2014 |
| Visual Reference Resolution using Attention Memory for Visual Dialog PH Seo, AM Lehrmann, B Han, L Sigal Advances in Neural Information Processing Systems (NeurIPS), 2017 | 87 | 2017 |
| Probabilistic Video Generation using Holistic Attribute Control J He, AM Lehrmann, J Marino, G Mori, L Sigal European Conference on Computer Vision (ECCV), 2018 | 51 | 2018 |
| A Non-parametric Bayesian Network Prior of Human Pose AM Lehrmann, PV Gehler, S Nowozin International Conference on Computer Vision (ICCV), 2013 | 43 | 2013 |
| Learning Physics-guided Face Relighting under Directional Light T Nestmeyer, JF Lalonde, I Matthews, AM Lehrmann Computer Vision and Pattern Recognition (CVPR), 2020 | 28 | 2020 |
| Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows R Deng, B Chang, MA Brubaker, G Mori, A Lehrmann Advances in Neural Information Processing Systems (NeurIPS), 2020 | 11 | 2020 |
| Visualizing Dimensionality Reduction of Systems Biology Data AM Lehrmann, M Huber, AC Polatkan, A Pritzkau, K Nieselt Data Mining and Knowledge Discovery, 2013 | 9 | 2013 |
| Variational Autoencoders with Jointly Optimized Latent Dependency Structure J He, Y Gong, J Marino, G Mori, AM Lehrmann International Conference on Learning Representations (ICLR), 2018 | 7 | 2018 |
| Generating Videos of Zero-Shot Compositions of Actions and Objects M Nawhal, M Zhai, A Lehrmann, L Sigal, G Mori European Conference on Computer Vision (ECCV), 2020 | 6* | 2020 |
| PROVIDE: A Probabilistic Framework for Unsupervised Video Decomposition P Zablotskaia, EA Dominici, L Sigal, AM Lehrmann Uncertainty in Artificial Intelligence (UAI), 2021 | 4* | 2021 |
| Non-parametric Structured Output Networks AM Lehrmann, L Sigal Advances in Neural Information Processing Systems (NeurIPS), 2017 | 4 | 2017 |
| System and Method of Analyzing Images using a Hierarchical Set of Models AM Lehrmann, L Sigal US Patent 10,163,036, 2018 | 1 | 2018 |
| Traversing the Continuous Spectrum of Image Retrieval with Deep Dynamic Models Z Al-Halah, AM Lehrmann, L Sigal arXiv preprint arXiv:1812.00202, 2018 | 1* | 2018 |
| Systems and methods for modeling continuous stochastic processes with dynamic normalizing flows D Ruizhi, B Chang, MA Brubaker, GP Mori, ASM Lehrmann US Patent App. 17/170,416, 2021 | | 2021 |
| Continuous Latent Process Flows R Deng, MA Brubaker, G Mori, AM Lehrmann arXiv preprint arXiv:2106.15580, 2021 | | 2021 |
| Agent Forecasting at Flexible Horizons using ODE Flows A Radovic, J He, J Ramanan, MA Brubaker, A Lehrmann ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | | 2021 |
| System and Method for Generation of Unseen Composite Data Objects M Nawhal, M Zhai, AM Lehrmann, L Sigal, G Mori US Patent App. 16/826,214, 2020 | | 2020 |
| Visual Reference Resolution using Attention Memory for Visual Dialog AM Lehrmann, PH Seo US Patent App. 15/884,339, 2019 | | 2019 |
| Non-parametric Models for Structured Data and Applications to Human Bodies and Natural Scenes AM Lehrmann ETH Zurich, 2016 | | 2016 |
Leonid SigalAssociate Professor, University of British ColumbiaBestätigte E-Mail-Adresse bei cs.ubc.ca
