8 citations · 16 across the 6 of their papers we have counts for
8 papers
Are Semi-Dense Detector-Free Methods Good at Matching Local Features?
Matthieu Vilain, Rémi Giraud, Hugo Germain +1
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 be…
Nerfels: Renderable Neural Codes for Improved Camera Pose Estimation
Gil Avraham, Julian Straub, Tianwei Shen +7
This paper presents a framework that combines traditional keypoint-based camera pose optimization with an invertible neural rendering mechanism. Our proposed 3D scene representatio…
Visual Correspondence Hallucination
Hugo Germain, Vincent Lepetit, Guillaume Bourmaud
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…
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
Paul-Edouard Sarlin, Ajaykumar Unagar, Måns Larsson +8
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, f…
Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation
Hugo Germain, Vincent Lepetit, Guillaume Bourmaud
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 corre…
S2DNet: Learning Accurate Correspondences for Sparse-to-Dense Feature Matching
Hugo Germain, Guillaume Bourmaud, Vincent Lepetit
Establishing robust and accurate correspondences is a fundamental backbone to many computer vision algorithms. While recent learning-based feature matching methods have shown promi…
Sparse-to-Dense Hypercolumn Matching for Long-Term Visual Localization
Hugo Germain, Guillaume Bourmaud, Vincent Lepetit
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 a…
Improving Nighttime Retrieval-Based Localization
Hugo Germain, Guillaume Bourmaud, Vincent Lepetit
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 str…