HOLI-1-to-3: Transient-Enhanced Holistic Image-to-3D Generation.

Abstract

We introduce HOLI-1-to-3, a novel technique for holistic 3D shape recovery from a single-viewpoint input, by effectively combining line-of-sight (LOS) and non-line-of-sight (NLOS) imaging. We leverage advancements in ultrafast time-of-flight (ToF) sensors and learning-based 3D shape inference techniques, such as diffusion models. HOLI-1-to-3 employs a new neural plenoptic representation, which unifies radiance fields (for LOS RGB images) and transient fields (for NLOS transients). HOLI-1-to-3 is optimized through a two-stage pipeline involving diffusion priors and transients prior. Our technique allows for accurate and continuous reconstruction of both visible and invisible parts of objects from a single view. Comprehensive experiments on both simulated and real-world datasets demonstrate the effectiveness of HOLI-1-to-3in resolving ambiguities in invisible parts of objects and significantly improving overall generation quality. The datasets used in our experiments will be made available to the research community to facilitate further achievements in holistic 3D shape recovery.