AI RESEARCH
UniFixer: A Universal Reference-Guided Fixer for Diffusion-Based View Synthesis
arXiv CS.CV
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ArXi:2605.12169v1 Announce Type: new With the recent surge of generative models, diffusion-based approaches have become mainstream for view synthesis tasks, either in an explicit depth-warp-inpaint or in an implicit end-to-end manner. Despite their success, both paradigms often suffer from noticeable quality degradation, e.g., blurred details and distorted structures, caused by pixel-to-latent compression and diffusion hallucination.