3 code implementations • 29 Jul 2017 • Edward Smith, David Meger
This paper describes a new approach for training generative adversarial networks (GAN) to understand the detailed 3D shape of objects.
3 code implementations • NeurIPS 2018 • Edward Smith, Scott Fujimoto, David Meger
We consider the problem of scaling deep generative shape models to high-resolution.
Ranked #2 on 3D Object Reconstruction on Data3D−R2N2 (Avg F1 metric)
6 code implementations • 12 Nov 2019 • Krishna Murthy Jatavallabhula, Edward Smith, Jean-Francois Lafleche, Clement Fuji Tsang, Artem Rozantsev, Wenzheng Chen, Tommy Xiang, Rev Lebaredian, Sanja Fidler
We present Kaolin, a PyTorch library aiming to accelerate 3D deep learning research.