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title
VGGSfM: Visual Geometry Grounded Deep Structure From Motion.
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We propose a new deep SfM pipeline VGGSfM, where each component is fully differentiable and thus can be trained in an end-to-end manner.
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author
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2026-02-22 14:00:36
raw text
VGGSfM: Visual Geometry Grounded Deep Structure From Motion VGGSfM: Visual Geometry Grounded Deep Structure From Motion Jianyuan Wang 1, 2 , Nikita Karaev 1, 2 , Christian Rupprecht 1 , David Novotny 2 1 Visual Geometry Group, University of Oxford, 2 Meta AI IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024, Highlight Paper Code 🤗 Demo Visualization of VGGSfM reconstructions from multiple observation angles. Abstract Structure-from-motion (SfM) is a long-standing problem in the computer vision community, which aims to reconstruct the camera poses and 3D structure of a scene from a set of unconstrained 2D images. Classical frameworks solve this problem in an incremental manner by detecting and matching keypoints, registering images, triangulating 3D points, and conducting bundle adjustment. Recent research efforts have predominantly revolved around harnessin...
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