64 citations · 168 across the 24 of their papers we have counts for
8 papers · 1 filter
Uncertainty-Driven Active Vision for Implicit Scene Reconstruction
Edward J. Smith, Michal Drozdzal, Derek Nowrouzezahrai +2
Multi-view implicit scene reconstruction methods have become increasingly popular due to their ability to represent complex scene details. Recent efforts have been devoted to impro…
Active 3D Shape Reconstruction from Vision and Touch
Edward J. Smith, David Meger, Luis Pineda +4
Humans build 3D understandings of the world through active object exploration, using jointly their senses of vision and touch. However, in 3D shape reconstruction, most recent prog…
3D Shape Reconstruction from Vision and Touch
Edward J. Smith, Roberto Calandra, Adriana Romero +4
When a toddler is presented a new toy, their instinctual behaviour is to pick it upand inspect it with their hand and eyes in tandem, clearly searching over its surface to properly…
Human Motion Prediction via Pattern Completion in Latent Representation Space
Yi Tian Xu, Yaqiao Li, David Meger
Inspired by ideas in cognitive science, we propose a novel and general approach to solve human motion understanding via pattern completion on a learned latent representation space.…
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Edward J. Smith, Scott Fujimoto, Adriana Romero +1
Mesh models are a promising approach for encoding the structure of 3D objects. Current mesh reconstruction systems predict uniformly distributed vertex locations of a predetermined…
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation
Edward Smith, Scott Fujimoto, David Meger
We consider the problem of scaling deep generative shape models to high-resolution. Drawing motivation from the canonical view representation of objects, we introduce a novel metho…