DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation

arXiv:2306.12422v2 Announce Type: replace-cross
Abstract: Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization process suffers slow convergence and the resultant 3D models often exhibit two limitations: (a) quality concerns such as missing attributes and distorted shape and texture; (b) extremely low diversity comparing to text-guided image synthesis. In this paper, we show that the conflict between the 3D optimization …

3d models abstract arxiv concerns convergence cs.cv cs.gr cs.lg differentiable diffusion diffusion models distillation however image image diffusion limitations optimization optimization strategy process quality representation strategy text text-to-image type