Feb. 20, 2024, 5:45 a.m. | Zhijun Pan, Fangqiang Ding, Hantao Zhong, Chris Xiaoxuan Lu

cs.LG updates on arXiv.org arxiv.org

arXiv:2309.09737v4 Announce Type: replace-cross
Abstract: Mobile autonomy relies on the precise perception of dynamic environments. Robustly tracking moving objects in 3D world thus plays a pivotal role for applications like trajectory prediction, obstacle avoidance, and path planning. While most current methods utilize LiDARs or cameras for Multiple Object Tracking (MOT), the capabilities of 4D imaging radars remain largely unexplored. Recognizing the challenges posed by radar noise and point sparsity in 4D radar data, we introduce RaTrack, an innovative solution tailored …

arxiv cloud cs.ai cs.cv cs.lg cs.ro detection moving radar tracking type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne