4 papers
Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving
Yang Wu, Qiang Meng, Zhaojiang Liu +3
Current end-to-end autonomous driving models are fundamentally constrained by the behavioral cloning ceiling of imitation learning. While reinforcement learning offers a path to sm…
GEM: Generating LiDAR World Model via Deformable Mamba
Yang Wu, Zhaojiang Liu, Qiang Meng +5
World models, which simulate environmental dynamics and generate sensor observations, are gaining increasing attention in autonomous driving. However, progress in LiDAR-based world…
CMF-IoU: Multi-Stage Cross-Modal Fusion 3D Object Detection with IoU Joint Prediction
Zhiwei Ning, Zhaojiang Liu, Xuanang Gao +4
Multi-modal methods based on camera and LiDAR sensors have garnered significant attention in the field of 3D detection. However, many prevalent works focus on single or partial sta…
OPUS: Occupancy Prediction Using a Sparse Set
Jiabao Wang, Zhaojiang Liu, Qiang Meng +6
Occupancy prediction, aiming at predicting the occupancy status within voxelized 3D environment, is quickly gaining momentum within the autonomous driving community. Mainstream occ…