AIBullisharXiv – CS AI · Mar 36/107
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ArtiFixer: Enhancing and Extending 3D Reconstruction with Auto-Regressive Diffusion Models
Researchers propose ArtiFixer, a two-stage pipeline using auto-regressive diffusion models to enhance 3D reconstruction quality. The method addresses scalability and quality issues in existing approaches by training a bidirectional generative model with opacity mixing, then distilling it into a causal auto-regressive model that generates hundreds of frames in a single pass.