3 citations · 4 across the 3 of their papers we have counts for
5 papers
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
Davis Rempe, Tolga Birdal, Yongheng Zhao +3
We propose CaSPR, a method to learn object-centric Canonical Spatiotemporal Point Cloud Representations of dynamically moving or evolving objects. Our goal is to enable information…
Contact and Human Dynamics from Monocular Video
Davis Rempe, Leonidas J. Guibas, Aaron Hertzmann +3
Existing deep models predict 2D and 3D kinematic poses from video that are approximately accurate, but contain visible errors that violate physical constraints, such as feet penetr…
Predicting the Physical Dynamics of Unseen 3D Objects
Davis Rempe, Srinath Sridhar, He Wang +1
Machines that can predict the effect of physical interactions on the dynamics of previously unseen object instances are important for creating better robots and interactive virtual…
Multiview Aggregation for Learning Category-Specific Shape Reconstruction
Srinath Sridhar, Davis Rempe, Julien Valentin +2
We investigate the problem of learning category-specific 3D shape reconstruction from a variable number of RGB views of previously unobserved object instances. Most approaches for…
Learning Generalizable Physical Dynamics of 3D Rigid Objects
Davis Rempe, Srinath Sridhar, He Wang +1
Humans have a remarkable ability to predict the effect of physical interactions on the dynamics of objects. Endowing machines with this ability would allow important applications i…