Scott Fujimoto, Edward J. Smith, Wei-Di Chang, Shixiang Shane Gu, Doina Precup, David Meger

For SALE: State-Action Representation Learning for Deep Reinforcement Learning

Edward J. Smith, Michal Drozdzal, Derek Nowrouzezahrai, David Meger, Adriana Romero-Soriano

Uncertainty-Driven Active Vision for Implicit Scene Reconstruction

Edward J. Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik, Adriana Romero, Michal Drozdzal

Active 3D Shape Reconstruction from Vision and Touch

Conference on Neural Information Processing Systems (NeurIPS), 2021

Edward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal

3D Shape Reconstruction from Vision and Touch

Conference on Neural Information Processing Systems (NeurIPS), 2020

Edward J. Smith, Krishna Murthy Jatavallabhula (Equal-first), Jean-Francois Lafleche, Clement Fuji Tsang, Artem Rozantsev, Wenzheng Chen, Tommy Xiang, Rev Lebaredian, Sanja Fidler

Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research

arXiv, 2019

Wenzheng Chen, Edward J. Smith*, Jun Gao*, Huan Ling*, Jaakko Lehtinen, Alec Jacobson, Sanja Fidler

Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer

Conference on Neural Information Processing Systems (NeurIPS), 2019

Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger

GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects

International Conference on Machine Learning (ICML), 2019

Edward J. Smith, Scott Fujimoto, David Meger

Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation

Conference on Neural Information Processing Systems (NIPS), 2018

Edward J. Smith, David Meger

Improved Adversarial Systems for 3D Object Generation and Reconstruction

Conference on Robot Learning (CoRL), 2017