Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability

arXiv:2402.12225v1 Announce Type: new
Abstract: Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D domains, and seek a stronger ability of 3D shape generation by improving auto-regressive models at capacity and scalability simultaneously. Firstly, we leverage an ensemble of publicly available 3D datasets to facilitate the training of large-scale models. It consists of a comprehensive collection of approximately 900,000 objects, with multiple properties …

2d image abstract arxiv auto capacity cs.cv domains grid image image generation modeling paper scalability space type