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20242026
most citedEvent-LAB: Towards Standardized Evaluation of Neuromorphic Localization Methods

1 citations · 1 across the 3 of their papers we have counts for

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cs.CV2026

Long-Term Multi-Session 3D Reconstruction Under Substantial Appearance Change

Beverley Gorry, Tobias Fischer, Michael Milford +1

Long-term environmental monitoring requires the ability to reconstruct and align 3D models across repeated site visits separated by months or years. However, existing Structure-fro…

cs.CV2026

Robust Scene Coordinate Regression via Geometrically-Consistent Global Descriptors

Son Tung Nguyen, Alejandro Fontan, Michael Milford +1

Recent learning-based visual localization methods use global descriptors to disambiguate visually similar places, but existing approaches often derive these descriptors from geomet…

cs.CV2025

FUSELOC: Fusing Global and Local Descriptors to Disambiguate 2D-3D Matching in Visual Localization

Son Tung Nguyen, Alejandro Fontan, Michael Milford +1

Hierarchical visual localization methods achieve state-of-the-art accuracy but require substantial memory as they need to store all database images. Direct 2D-3D matching requires…

cs.CV2025

VSLAM-LAB: A Comprehensive Framework for Visual SLAM Methods and Datasets

Alejandro Fontan, Tobias Fischer, Javier Civera +1

Visual Simultaneous Localization and Mapping (VSLAM) research faces significant challenges due to fragmented toolchains, complex system configurations, and inconsistent evaluation…

cs.CV2024

Look Ma, No Ground Truth! Ground-Truth-Free Tuning of Structure from Motion and Visual SLAM

Alejandro Fontan, Javier Civera, Tobias Fischer +1

Evaluation is critical to both developing and tuning Structure from Motion (SfM) and Visual SLAM (VSLAM) systems, but is universally reliant on high-quality geometric ground truth…