5 citations · 5 across the 6 of their papers we have counts for
6 papers
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…
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.…
RGM: Reconstructing High-fidelity 3D Car Assets with Relightable 3D-GS Generative Model from a Single Image
Xiaoxue Chen, Jv Zheng, Hao Huang +8
The generation of high-quality 3D car assets is essential for various applications, including video games, autonomous driving, and virtual reality. Current 3D generation methods ut…
SA-GS: Scale-Adaptive Gaussian Splatting for Training-Free Anti-Aliasing
Xiaowei Song, Jv Zheng, Shiran Yuan +5
In this paper, we present a Scale-adaptive method for Anti-aliasing Gaussian Splatting (SA-GS). While the state-of-the-art method Mip-Splatting needs modifying the training procedu…