202 citations · 204 across the 4 of their papers we have counts for
4 papers
R4Det: 4D Radar-Camera Fusion for High-Performance 3D Object Detection
Zhongyu Xia, Yousen Tang, Yongtao Wang +2
4D radar-camera sensing configuration has gained increasing importance in autonomous driving. However, existing 3D object detection methods that fuse 4D Radar and camera data confr…
InsFusion: Rethink Instance-level LiDAR-Camera Fusion for 3D Object Detection
Zhongyu Xia, Hansong Yang, Yongtao Wang
Three-dimensional Object Detection from multi-view cameras and LiDAR is a crucial component for autonomous driving and smart transportation. However, in the process of basic featur…
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection
Kaicheng Yu, Tang Tao, Hongwei Xie +10
There are two critical sensors for 3D perception in autonomous driving, the camera and the LiDAR. The camera provides rich semantic information such as color, texture, and the LiDA…
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Tingting Liang, Hongwei Xie, Kaicheng Yu +6
Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to lever…