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Leonard Bruns

6 accepted papers

2025

ACE-G: Improving Generalization of Scene Coordinate Regression Through Query Pre-Training

Leonard Bruns, Axel Barroso-Laguna, Tommaso Cavallari, Aron Monszpart, Sowmya Munukutla, Victor Adrian Prisacariu +1
ICCV 2025poster

Scene coordinate regression (SCR) has established itself as a promising learning-based approach to visual relocalization. After mere minutes of scene-specific training, SCR models estimate camera poses of query images with high accuracy. Still, SCR methods fall short of the generalization capabiliti…

Cited by 0Source ↗PDF ↗Scholar ↗
2024

Conditional Variational Autoencoders for Probabilistic Pose Regression

Fereidoon Zangeneh, Leonard Bruns, Amit Dekel, Alessandro Pieropan, Patric Jensfelt
IROS 2024poster

Robots rely on visual relocalization to estimate their pose from camera images when they lose track. One of the challenges in visual relocalization is repetitive structures in the operation environment of the robot. This calls for probabilistic methods that support multiple hypotheses for robot’s po…

Cited by 1Source ↗Scholar ↗
2023

A Probabilistic Framework for Visual Localization in Ambiguous Scenes

Fereidoon Zangeneh, Leonard Bruns, Amit Dekel, Alessandro Pieropan, Patric Jensfelt
ICRA 2023poster

Visual localization allows autonomous robots to relocalize when losing track of their pose by matching their current observation with past ones. However, ambiguous scenes pose a challenge for such systems, as repetitive structures can be viewed from many distinct, equally likely camera poses, which…

Cited by 15Source ↗code ↗Scholar ↗
2022

SDFEst: Categorical Pose and Shape Estimation of Objects From RGB-D Using Signed Distance Fields

Leonard Bruns, Patric Jensfelt
RA-L 2022

Rich geometric understanding of the world is an important component of many robotic applications such as planning and manipulation. In this paper, we present a modular pipeline for pose and shape estimation of objects from RGB-D images given their category. The core of our method is a generative sha

Cited by 13Source ↗code ↗Scholar ↗
2021

Bench-MR: A Motion Planning Benchmark for Wheeled Mobile Robots

Eric Heiden, Luigi Palmieri, Leonard Bruns, Kai O. Arras, Gaurav S. Sukhatme, Sven Koenig
RA-L 2021

Planning smooth and energy-efficient paths for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, several sampling-based motion-planning algorithms, extend functions and post-smoothing algorithms have

Cited by 49Source ↗Scholar ↗