5 papers
CLRNet: Targetless Extrinsic Calibration for Camera, Lidar and 4D Radar Using Deep Learning
Marcell Kegl, Andras Palffy, Csaba Benedek +1
In this paper, we address extrinsic calibration for camera, lidar, and 4D radar sensors. Accurate extrinsic calibration of radar remains a challenge due to the sparsity of its data…
DRIFT: Dual-Representation Inter-Fusion Transformer for Automated Driving Perception with 4D Radar Point Clouds
Siqi Pei, Andras Palffy, Dariu M. Gavrila
4D radars, which provide 3D point cloud data along with Doppler velocity, are attractive components of modern automated driving systems due to their low cost and robustness under a…
4DRC-OCC: Robust Semantic Occupancy Prediction Through Fusion of 4D Radar and Camera
David Ninfa, Andras Palffy, Holger Caesar
Autonomous driving requires robust perception across diverse environmental conditions, yet 3D semantic occupancy prediction remains challenging under adverse weather and lighting.…
4D-RaDiff: Latent Diffusion for 4D Radar Point Cloud Generation
Jimmie Kwok, Holger Caesar, Andras Palffy
Automotive radar has shown promising developments in environment perception due to its cost-effectiveness and robustness in adverse weather conditions. However, the limited availab…
LeAP: Consistent multi-domain 3D labeling using Foundation Models
Simon Gebraad, Andras Palffy, Holger Caesar
Availability of datasets is a strong driver for research on 3D semantic understanding, and whilst obtaining unlabeled 3D point cloud data is straightforward, manually annotating th…