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Autoregressive 3D layout generation can be both more physically plausible and significantly faster by repurposing existing 3D generative models.
Reconstructing 3D scenes from images obscured by smoke and extreme darkness is now significantly more achievable, thanks to insights gleaned from the NTIRE 2026 challenge.
Unlock high-quality 3D part segmentation with minimal labeled data by repurposing existing 3D generative models.
