activity
20232026
most citedDo we need scan-matching in radar odometry?

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Dense Dynamic Scene Reconstruction and Camera Pose Estimation from Multi-View Videos

Shuo Sun, Unal Artan, Malcolm Mielle +3

We address the challenging problem of dense dynamic scene reconstruction and camera pose estimation from multiple freely moving cameras -- a setting that arises naturally when mult…

cs.RO2026

Neural Surface and Reflectance Modelling from 3D Radar Data

Judith Treffler, Vladimír Kubelka, Henrik Andreasson +1

Robust scene representation is essential for autonomous systems to safely operate in challenging low-visibility environments. In these conditions, radar has a clear advantage over…

cs.CV2024★ 1 cited

4D Radar Semantic Segmentation of People in Field Conditions Using Temporal Multi-View Networks

Mikael Skog, Oleksandr Kotlyar, Vladimír Kubelka +1

Reliable people detection is crucial for the safe autonomy of mobile robots and heavy vehicles, both on roads and in industrial settings like mining and construction. However, comm…

cs.RO2023★ 1 cited

Do we need scan-matching in radar odometry?

Vladimír Kubelka, Emil Fritz, Martin Magnusson

There is a current increase in the development of "4D" Doppler-capable radar and lidar range sensors that produce 3D point clouds where all points also have information about the r…

cs.RO2023

Doppler-only Single-scan 3D Vehicle Odometry

Andres Galeote-Luque, Vladimír Kubelka, Martin Magnusson +2

We present a novel 3D odometry method that recovers the full motion of a vehicle only from a Doppler-capable range sensor. It leverages the radial velocities measured from the scen…