UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion

arXiv:2404.06851v1 Announce Type: new
Abstract: Diffusion models have shown remarkable results for image generation, editing and inpainting. Recent works explore diffusion models for 3D shape generation with neural implicit functions, i.e., signed distance function and occupancy function. However, they are limited to shapes with closed surfaces, which prevents them from generating diverse 3D real-world contents containing open surfaces. In this work, we present UDiFF, a 3D diffusion model for unsigned distance fields (UDFs) which is capable to generate textured 3D …

arxiv cs.cv diffusion fields type wavelet