4 papers
CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving
Zhennan Wang, Jianing Teng, Canqun Xiang +4
While end-to-end autonomous driving has advanced significantly, prevailing methods remain fundamentally misaligned with human cognitive principles in both perception and planning.…
Distilling Future Temporal Knowledge with Masked Feature Reconstruction for 3D Object Detection
Haowen Zheng, Hu Zhu, Lu Deng +3
Camera-based temporal 3D object detection has shown impressive results in autonomous driving, with offline models improving accuracy by using future frames. Knowledge distillation…
HMVLM: Multistage Reasoning-Enhanced Vision-Language Model for Long-Tailed Driving Scenarios
Daming Wang, Yuhao Song, Zijian He +4
We present HaoMo Vision-Language Model (HMVLM), an end-to-end driving framework that implements the slow branch of a cognitively inspired fast-slow architecture. A fast controller…
HMAD: Advancing E2E Driving with Anchored Offset Proposals and Simulation-Supervised Multi-target Scoring
Bin Wang, Pingjun Li, Jinkun Liu +7
End-to-end autonomous driving faces persistent challenges in both generating diverse, rule-compliant trajectories and robustly selecting the optimal path from these options via lea…