Research interests
I'm generally interested in 3D computer vision and machine learning, particularly in understanding dynamic and physical objects, humans, and scenes.
Recent publications
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Davis Rempe, Jonah Philion, Leonidas J. Guibas, Sanja Fidler, Or Litany, Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior, Conference on Computer Vision and Pattern Recognition (CVPR), 2022
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Davis Rempe, Tolga Birdal, Aaron Hertzmann, Jimei Yang, Srinath Sridhar, Leonidas J. Guibas, HuMoR: 3D Human Motion Model for Robust Pose Estimation, International Conference on Computer Vision (ICCV), 2021 (Oral)
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Ali Kashefi, Davis Rempe, Leonidas J. Guibas, A point-cloud deep learning framework for prediction of fluid flow fields on irregular geometries, Physics of Fluids 33:2, 2021
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Davis Rempe, Tolga Birdal, Yongheng Zhao, Zan Gojcic, Srinath Sridhar, Leonidas J. Guibas, CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations, Advances in Neural Information Processing Systems (NeurIPS), 2020 (Spotlight).
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Davis Rempe, Leonidas J. Guibas, Aaron Hertzmann, Bryan Russell, Ruben Villegas, and Jimei Yang, Contact and Human Dynamics from Monocular Video, European Conference on Computer Vision (ECCV), 2020 (Spotlight).
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Davis Rempe, Srinath Sridhar, He Wang, and Leonidas J. Guibas, Predicting the Physical Dynamics of Unseen 3D Objects, IEEE Winter Conference on Applications of Computer Vision (WACV), 2020.
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Learning Generalizable Final-State Dynamics of 3D Rigid Objects, Davis Rempe, Srinath Sridhar, He Wang, and Leonidas J. Guibas, CVPR Workshop on 3D Scene Understanding for Vision, Graphics, and Robotics, 2019.
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Learning Generalizable Physical Dynamics of 3D Rigid Objects
Davis Rempe, Srinath Sridhar, He Wang, Leonidas J. Guibas. arXiv preprint, arXiv:1901.00466, 2019.
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