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20222026
most citedVehicle-to-Everything Cooperative Perception for Autonomous Driving

48 citations · 63 across the 15 of their papers we have counts for

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10 papers · 1 filter

cs.CV2026

Wavelet-based Multi-View Fusion of 4D Radar Tensor and Camera for Robust 3D Object Detection

Runwei Guan, Jianan Liu, Shaofeng Liang +7

4D millimeter-wave (mmWave) radar has been widely adopted in autonomous driving and robot perception due to its low cost and all-weather robustness. However, point-cloud-based rada…

cs.CV2025

RaGS: Unleashing 3D Gaussian Splatting from 4D Radar and Monocular Cues for 3D Object Detection

Xiaokai Bai, Chenxu Zhou, Lianqing Zheng +6

4D millimeter-wave radar is a promising sensing modality for autonomous driving, yet effective 3D object detection from 4D radar and monocular images remains challenging. Existing…

cs.CV2025

MS-Occ: Multi-Stage LiDAR-Camera Fusion for 3D Semantic Occupancy Prediction

Zhiqiang Wei, Lianqing Zheng, Jianan Liu +4

Accurate 3D semantic occupancy perception is essential for autonomous driving in complex environments with diverse and irregular objects. While vision-centric methods suffer from g…

cs.CV2025

Talk2PC: Enhancing 3D Visual Grounding through LiDAR and Radar Point Clouds Fusion for Autonomous Driving

Runwei Guan, Jianan Liu, Ningwei Ouyang +8

Embodied outdoor scene understanding forms the foundation for autonomous agents to perceive, analyze, and react to dynamic driving environments. However, existing 3D understanding…

cs.CV2025

Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perception

Lianqing Zheng, Jianan Liu, Runwei Guan +8

3D object detection and occupancy prediction are critical tasks in autonomous driving, attracting significant attention. Despite the potential of recent vision-based methods, they…

cs.CV2024

OmniHD-Scenes: A Next-Generation Multimodal Dataset for Autonomous Driving

Lianqing Zheng, Long Yang, Qunshu Lin +10

The rapid advancement of deep learning has intensified the need for comprehensive data for use by autonomous driving algorithms. High-quality datasets are crucial for the developme…

cs.CV2024

NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar

Runwei Guan, Jianan Liu, Liye Jia +7

Recently, visual grounding and multi-sensors setting have been incorporated into perception system for terrestrial autonomous driving systems and Unmanned Surface Vehicles (USVs),…

cs.CV2023★ 48 cited

Vehicle-to-Everything Cooperative Perception for Autonomous Driving

Tao Huang, Jianan Liu, Xi Zhou +5

Achieving fully autonomous driving with enhanced safety and efficiency relies on vehicle-to-everything cooperative perception, which enables vehicles to share perception data, ther…

cs.CV2023★ 3 cited

LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Clouds

Zhenrong Zhang, Jianan Liu, Yuxuan Xia +3

Online multi-object tracking (MOT) plays a pivotal role in autonomous systems. The state-of-the-art approaches usually employ a tracking-by-detection method, and data association p…

cs.CV2022★ 6 cited

RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems

Yanlong Yang, Jianan Liu, Tao Huang +3

In autonomous driving, LiDAR and radar are crucial for environmental perception. LiDAR offers precise 3D spatial sensing information but struggles in adverse weather like fog. Conv…