9 papers
Talk2Sensors: 3D Visual Grounding in Autonomous Driving via Sensor-Adaptive Physical Cue Matching
Runwei Guan, Di Tian, Ningwei Ouyang +9
As a key capability for embodied intelligence, 3D visual grounding (3DVG) has been predominantly studied in indoor scenes with RGB-D or point-cloud inputs, while existing outdoor e…
4DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene Perception
Xiaokai Bai, Lianqing Zheng, Runwei Guan +3
Reliable autonomous driving requires full-scene perception that couples foreground objects with dense semantic layout. Recently, 4D millimeter-wave radar has emerged as a robust an…
RC-GeoCP: Geometric Consensus for 4D Radar-Camera Collaborative Perception
Xiaokai Bai, Lianqing Zheng, Runwei Guan +3
Collaborative perception (CP) extends sensing range through feature sharing, but most systems remain LiDAR-centric. Camera and 4D radar sensing combines dense semantics with lower-…
SD4R: Sparse-to-Dense Learning for 3D Object Detection with 4D Radar
Xiaokai Bai, Jiahao Cheng, Songkai Wang +5
4D radar measurements offer an affordable and weather-robust solution for 3D perception. However, the inherent sparsity and noise of radar point clouds present significant challeng…
Boosting Instance Awareness via Cross-View Correlation with 4D Radar and Camera for 3D Object Detection
Xiaokai Bai, Lianqing Zheng, Si-Yuan Cao +6
4D millimeter-wave radar has emerged as a promising sensing modality for autonomous driving due to its robustness and affordability. However, its sparse and weak geometric cues mak…
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…
TDFANet: Encoding Sequential 4D Radar Point Clouds Using Trajectory-Guided Deformable Feature Aggregation for Place Recognition
Shouyi Lu, Guirong Zhuo, Haitao Wang +6
Place recognition is essential for achieving closed-loop or global positioning in autonomous vehicles and mobile robots. Despite recent advancements in place recognition using 2D c…
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…
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…