290 citations · 384 across the 14 of their papers we have counts for
4 papers · 1 filter
A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries
Ali Kashefi, Davis Rempe, Leonidas J. Guibas
We present a novel deep learning framework for flow field predictions in irregular domains when the solution is a function of the geometry of either the domain or objects inside th…
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…