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pro vyhledávání: '"Germain, Hugo"'
Autor:
Bochkovskii, Aleksei, Delaunoy, Amaël, Germain, Hugo, Santos, Marcel, Zhou, Yichao, Richter, Stephan R., Koltun, Vladlen
We present a foundation model for zero-shot metric monocular depth estimation. Our model, Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high-frequency details. The predictions are metric, with absolute scale, witho
Externí odkaz:
http://arxiv.org/abs/2410.02073
Semi-dense detector-free approaches (SDF), such as LoFTR, are currently among the most popular image matching methods. While SDF methods are trained to establish correspondences between two images, their performances are almost exclusively evaluated
Externí odkaz:
http://arxiv.org/abs/2402.08671
Autor:
Avraham, Gil, Straub, Julian, Shen, Tianwei, Yang, Tsun-Yi, Germain, Hugo, Sweeney, Chris, Balntas, Vasileios, Novotny, David, DeTone, Daniel, Newcombe, Richard
This paper presents a framework that combines traditional keypoint-based camera pose optimization with an invertible neural rendering mechanism. Our proposed 3D scene representation, Nerfels, is locally dense yet globally sparse. As opposed to existi
Externí odkaz:
http://arxiv.org/abs/2206.01916
Given a pair of partially overlapping source and target images and a keypoint in the source image, the keypoint's correspondent in the target image can be either visible, occluded or outside the field of view. Local feature matching methods are only
Externí odkaz:
http://arxiv.org/abs/2106.09711
Autor:
Sarlin, Paul-Edouard, Unagar, Ajaykumar, Larsson, Måns, Germain, Hugo, Toft, Carl, Larsson, Viktor, Pollefeys, Marc, Lepetit, Vincent, Hammarstrand, Lars, Kahl, Fredrik, Sattler, Torsten
Camera pose estimation in known scenes is a 3D geometry task recently tackled by multiple learning algorithms. Many regress precise geometric quantities, like poses or 3D points, from an input image. This either fails to generalize to new viewpoints
Externí odkaz:
http://arxiv.org/abs/2103.09213
Absolute camera pose estimation is usually addressed by sequentially solving two distinct subproblems: First a feature matching problem that seeks to establish putative 2D-3D correspondences, and then a Perspective-n-Point problem that minimizes, wit
Externí odkaz:
http://arxiv.org/abs/2103.07153
Establishing robust and accurate correspondences is a fundamental backbone to many computer vision algorithms. While recent learning-based feature matching methods have shown promising results in providing robust correspondences under challenging con
Externí odkaz:
http://arxiv.org/abs/2004.01673
We propose a novel approach to feature point matching, suitable for robust and accurate outdoor visual localization in long-term scenarios. Given a query image, we first match it against a database of registered reference images, using recent retriev
Externí odkaz:
http://arxiv.org/abs/1907.03965
Outdoor visual localization is a crucial component to many computer vision systems. We propose an approach to localization from images that is designed to explicitly handle the strong variations in appearance happening between daytime and nighttime.
Externí odkaz:
http://arxiv.org/abs/1812.03707
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