Nov. 5, 2023, 6:49 a.m. | Jen-Hao Cheng, Sheng-Yao Kuan, Hugo Latapie, Gaowen Liu, Jenq-Neng Hwang

cs.CV updates on arXiv.org arxiv.org

Robust perception is a vital component for ensuring safe autonomous and
assisted driving. Automotive radar (77 to 81 GHz), which offers
weather-resilient sensing, provides a complementary capability to the vision-
or LiDAR-based autonomous driving systems. Raw radio-frequency (RF) radar
tensors contain rich spatiotemporal semantics besides 3D location information.
The majority of previous methods take in 3D (Doppler-range-azimuth) RF radar
tensors, allowing prediction of an object's location, heading angle, and size
in bird's-eye-view (BEV). However, they lack the ability to at …

3d object detection arxiv automotive autonomous autonomous driving autonomous driving systems capability detection driving framework lidar perception radar radio raw resilient semantics sensing systems tracking vision vital weather

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