activity
20182021
most citedS2DNet: Learning Accurate Correspondences for Sparse-to-Dense Feature Matching

8 citations · 9 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20211 cited

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…

cs.CV2021

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…

cs.CV20208 cited

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…

cs.CV2019

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…

cs.CV2018

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…