3 papers
cs.CV2026
RaCo: Ranking and Covariance for Practical Learned Keypoints
Abhiram Shenoi, Philipp Lindenberger, Paul-Edouard Sarlin +1
This paper introduces RaCo, a lightweight neural network designed to learn robust and versatile keypoints suitable for a variety of 3D computer vision tasks. The model integrates t…
cs.CV2025
Scaling Image Geo-Localization to Continent Level
Philipp Lindenberger, Paul-Edouard Sarlin, Jan Hosang +4
Determining the precise geographic location of an image at a global scale remains an unsolved challenge. Standard image retrieval techniques are inefficient due to the sheer volume…
cs.CV2024
GeoCalib: Learning Single-image Calibration with Geometric Optimization
Alexander Veicht, Paul-Edouard Sarlin, Philipp Lindenberger +1
From a single image, visual cues can help deduce intrinsic and extrinsic camera parameters like the focal length and the gravity direction. This single-image calibration can benefi…