activity
20172026
most citedmaplab: An Open Framework for Research in Visual-inertial Mapping and Localization

281 citations · 284 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV2026

KilometerVision: A New Frontier for Large-Scale Spatial Intelligence in VLMs

Aravindh Mahendran, Michael King, Matthew Koichi Grimes +12

We push the frontier of large-scale spatial intelligence in Vision-Language Models (VLMs) and introduce the first benchmark that probes geographical layout understanding from real-…

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.CV2023

Yes, we CANN: Constrained Approximate Nearest Neighbors for local feature-based visual localization

Dror Aiger, André Araujo, Simon Lynen

Large-scale visual localization systems continue to rely on 3D point clouds built from image collections using structure-from-motion. While the 3D points in these models are repres…

cs.CV2023★ 3 cited

SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding

Paul-Edouard Sarlin, Eduard Trulls, Marc Pollefeys +2

Semantic 2D maps are commonly used by humans and machines for navigation purposes, whether it's walking or driving. However, these maps have limitations: they lack detail, often co…

cs.CV2021

Efficient Large Scale Inlier Voting for Geometric Vision Problems

Dror Aiger, Simon Lynen, Jan Hosang +1

Outlier rejection and equivalently inlier set optimization is a key ingredient in numerous applications in computer vision such as filtering point-matches in camera pose estimation…

cs.CV2019

SuperNCN: Neighbourhood consensus network for robust outdoor scenes matching

Grzegorz Kurzejamski, Jacek Komorowski, Lukasz Dabala +3

In this paper, we present a framework for computing dense keypoint correspondences between images under strong scene appearance changes. Traditional methods, based on nearest neigh…