AI RESEARCH

Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering

arXiv CS.CV

ArXi:2508.14461v3 Announce Type: replace While multi-step diffusion models have advanced both forward and inverse rendering, existing approaches often treat these problems independently, leading to cycle inconsistency and slow inference speed. In this work, we present Ouroboros, a framework composed of two single-step diffusion models that handle forward and inverse rendering with mutual reinforcement. Our approach extends intrinsic decomposition to both indoor and outdoor scenes and