mlsanityData to 7 Oct 2026

Recovering Detail in 3D Shapes Using Disparity Maps

arXiv 2207.00182 ↗First posted 1 Jul 2022cs.CVcited by 0

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Abstract (arXiv)

We present a fine-tuning method to improve the appearance of 3D geometries reconstructed from single images. We leverage advances in monocular depth estimation to obtain disparity maps and present a novel approach to transforming 2D normalized disparity maps into 3D point clouds by using shape priors to solve an optimization on the relevant camera parameters. After creating a 3D point cloud from disparity, we introduce a method to combine the new point cloud with existing information to form a more faithful and detailed final geometry. We demonstrate the efficacy of our approach with multiple experiments on both synthetic and real images.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 44 of its 64 references that are in the map. First posted on arXiv 1 Jul 2022.

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44 of 64 references.

References · 44

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32 more
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