Point Cloud GAN

Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov

Abstract: We propose a GAN variant which learns to generate point clouds. Different studies have been explores, including tighter Wasserstein distance estimate, conditional generation, generalization to unseen point clouds and image to point cloud.