Dense-SfM: Structure from Motion with Dense Consistent Matching

JongMin Lee; Sungjoo Yoo

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arXiv · 2501.14277

Dense-SfM: Structure from Motion with Dense Consistent Matching

JongMin Lee·Sungjoo Yoo

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Abstract

We present Dense-SfM, a novel Structure from Motion (SfM) framework designed for dense and accurate 3D reconstruction from multi-view images. Sparse keypoint matching, which traditional SfM methods often rely on, limits both accuracy and point density, especially in texture-less areas. Dense-SfM addresses this limitation by integrating dense matching with a Gaussian Splatting (GS) based track extension which gives more consistent, longer feature tracks. To further improve reconstruction accuracy, Dense-SfM is equipped with a multi-view kernelized matching module leveraging transformer and Gaussian Process architectures, for robust track refinement across multi-views. Evaluations on the ETH3D and Texture-Poor SfM datasets show that Dense-SfM offers significant improvements in accuracy and density over state-of-the-art methods. Project page: https://icetea-cv.github.io/densesfm/.

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BibTeX RIS

JongMin Lee, Sungjoo Yoo. 2025-01-24. Dense-SfM: Structure from Motion with Dense Consistent Matching. https://arxiv.org/abs/2501.14277

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