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Sparse view reconstruction via diffusion distillation.
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2026-02-19 21:34:25
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SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction Zhizhuo Zhou , Shubham Tulsiani Carnegie Mellon University CVPR 2023 Paper Code SparseFusion reconstructs a consistent and realistic 3D neural scene representation from as few as 2 input images with known relative pose, while being able to generate detailed and plausible structures in uncertain or unobserved regions (such as front of the hydrant, teddybear's face, back of the laptop, or left side of the toybus). We show selected results below and random results here . Abstract We propose SparseFusion , a sparse view 3D reconstruction approach that unifies recent advances in neural rendering and probabilistic image generation. Existing approaches typically build on neural rendering with re-projected features but fail to generate unseen regions or handle uncertainty under large viewpoin...
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