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ORCIDAndreas M. Lehrmann
Person information
- affiliation: Facebook Reality Labs, Pittsburgh, PA, USA
- affiliation: Disney Research, Pittsburgh, PA, USA
- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
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2020 – today
- 2022
[j3]Chandramouli Shama Sastry, Andreas M. Lehrmann, Marcus A. Brubaker, Alexander Radovic:
Efficient CDF Approximations for Normalizing Flows. Trans. Mach. Learn. Res. 2022 (2022)- [i11]Chandramouli Shama Sastry, Andreas M. Lehrmann, Marcus A. Brubaker, Alexander Radovic:
Efficient CDF Approximations for Normalizing Flows. CoRR abs/2202.11322 (2022) - [i10]Ruizhi Deng, Greg Mori, Andreas M. Lehrmann:
Continuous-time Particle Filtering for Latent Stochastic Differential Equations. CoRR abs/2209.00173 (2022) - 2021
- [c11]Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann:
Continuous Latent Process Flows. NeurIPS 2021: 5162-5173 - [c10]Polina Zablotskaia, Edoardo A. Dominici
, Leonid Sigal, Andreas M. Lehrmann:
PROVIDE: a probabilistic framework for unsupervised video decomposition. UAI 2021: 2019-2028 - [i9]Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann:
Continuous Latent Process Flows. CoRR abs/2106.15580 (2021) - 2020
- [c9]Thomas Nestmeyer, Jean-François Lalonde, Iain A. Matthews, Andreas M. Lehrmann:
Learning Physics-Guided Face Relighting Under Directional Light. CVPR 2020: 5123-5132 - [c8]Megha Nawhal, Mengyao Zhai, Andreas M. Lehrmann, Leonid Sigal, Greg Mori:
Generating Videos of Zero-Shot Compositions of Actions and Objects. ECCV (12) 2020: 382-401 - [c7]Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann:
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. NeurIPS 2020 - [i8]Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann:
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. CoRR abs/2002.10516 (2020) - [i7]Polina Zablotskaia, Edoardo A. Dominici, Leonid Sigal, Andreas M. Lehrmann:
Unsupervised Video Decomposition using Spatio-temporal Iterative Inference. CoRR abs/2006.14727 (2020)
2010 – 2019
- 2019
- [j2]Stephen Lombardi, Tomas Simon, Jason M. Saragih, Gabriel Schwartz, Andreas M. Lehrmann, Yaser Sheikh:
Neural volumes: learning dynamic renderable volumes from images. ACM Trans. Graph. 38(4): 65:1-65:14 (2019) - [c6]Jiawei He, Yu Gong, Joseph Marino, Greg Mori, Andreas M. Lehrmann:
Variational Autoencoders with Jointly Optimized Latent Dependency Structure. ICLR (Poster) 2019 - [i6]Thomas Nestmeyer, Iain A. Matthews, Jean-François Lalonde, Andreas M. Lehrmann:
Structural Decompositions for End-to-End Relighting. CoRR abs/1906.03355 (2019) - [i5]Stephen Lombardi, Tomas Simon, Jason M. Saragih, Gabriel Schwartz, Andreas M. Lehrmann, Yaser Sheikh:
Neural Volumes: Learning Dynamic Renderable Volumes from Images. CoRR abs/1906.07751 (2019) - [i4]Megha Nawhal, Mengyao Zhai, Andreas M. Lehrmann, Leonid Sigal:
Zero-Shot Generation of Human-Object Interaction Videos. CoRR abs/1912.02401 (2019) - 2018
- [c5]Jiawei He, Andreas M. Lehrmann, Joseph Marino, Greg Mori, Leonid Sigal:
Probabilistic Video Generation Using Holistic Attribute Control. ECCV (5) 2018: 466-483 - [i3]Jiawei He, Andreas M. Lehrmann, Joseph Marino, Greg Mori, Leonid Sigal:
Probabilistic Video Generation using Holistic Attribute Control. CoRR abs/1803.08085 (2018) - [i2]Ziad Al-Halah, Andreas M. Lehrmann, Leonid Sigal:
Towards Traversing the Continuous Spectrum of Image Retrieval. CoRR abs/1812.00202 (2018) - 2017
- [c4]Paul Hongsuck Seo, Andreas M. Lehrmann, Bohyung Han, Leonid Sigal:
Visual Reference Resolution using Attention Memory for Visual Dialog. NIPS 2017: 3719-3729 - [c3]Andreas M. Lehrmann, Leonid Sigal:
Non-parametric Structured Output Networks. NIPS 2017: 4214-4224 - [i1]Paul Hongsuck Seo, Andreas M. Lehrmann, Bohyung Han, Leonid Sigal:
Visual Reference Resolution using Attention Memory for Visual Dialog. CoRR abs/1709.07992 (2017) - 2016
- [b1]Andreas M. Lehrmann:
Non-parametric models for structured data and applications to human bodies and natural scenes. ETH Zurich, Zürich, Switzerland, 2016 - 2014
- [c2]Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin:
Efficient Nonlinear Markov Models for Human Motion. CVPR 2014: 1314-1321 - 2013
- [j1]Andreas M. Lehrmann, Michael Huber, Aydin Can Polatkan, Albert Pritzkau, Kay Nieselt:
Visualizing dimensionality reduction of systems biology data. Data Min. Knowl. Discov. 27(1): 146-165 (2013) - [c1]Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin:
A Non-parametric Bayesian Network Prior of Human Pose. ICCV 2013: 1281-1288
Coauthor Index
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