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20212026
most citedLXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion

111 citations · 234 across the 8 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

RCGDet3D: Rethinking 4D Radar-Camera Fusion-based 3D Object Detection with Enhanced Radar Feature Encoding

Weiyi Xiong, Bing Zhu

4D automotive radar is indispensable for autonomous driving due to its low cost and robustness, yet its point cloud sparsity challenges 3D object detection. Existing 4D radar-camer…

cs.CV2025★ 1 cited

RadarGaussianDet3D: Gaussian Representation-based Real-time 3D Object Detection with 4D Automotive Radars

Weiyi Xiong, Bing Zhu, Zewei Zheng

4D automotive radars have gained increasing attention for autonomous driving due to their low cost, robustness, and inherent velocity measurement capability. However, existing 4D r…

cs.CV2025★ 17 cited

LXLv2: Enhanced LiDAR Excluded Lean 3D Object Detection with Fusion of 4D Radar and Camera

Weiyi Xiong, Zean Zou, Qiuchi Zhao +2

As the previous state-of-the-art 4D radar-camera fusion-based 3D object detection method, LXL utilizes the predicted image depth distribution maps and radar 3D occupancy grids to a…

cs.CV2024★ 10 cited

ProbRadarM3F: mmWave Radar based Human Skeletal Pose Estimation with Probability Map Guided Multi-Format Feature Fusion

Bing Zhu, Zixin He, Weiyi Xiong +3

Millimeter wave (mmWave) radar is a non-intrusive privacy and relatively convenient and inexpensive device, which has been demonstrated to be applicable in place of RGB cameras in…

cs.CV2023★ 2 cited

SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar

Jianan Liu, Qiuchi Zhao, Weiyi Xiong +3

The 4D Millimeter wave (mmWave) radar is a promising technology for vehicle sensing due to its cost-effectiveness and operability in adverse weather conditions. However, the adopti…

cs.CV2023★ 111 cited

LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion

Weiyi Xiong, Jianan Liu, Tao Huang +3

As an emerging technology and a relatively affordable device, the 4D imaging radar has already been confirmed effective in performing 3D object detection in autonomous driving. Nev…

cs.CV2022★ 22 cited

Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation

Weiyi Xiong, Jianan Liu, Yuxuan Xia +3

The automotive mmWave radar plays a key role in advanced driver assistance systems (ADAS) and autonomous driving. Deep learning-based instance segmentation enables real-time object…

cs.CV2021★ 71 cited

Deep Instance Segmentation with Automotive Radar Detection Points

Jianan Liu, Weiyi Xiong, Liping Bai +4

Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the spar…