arXiv AI
Jul 7

BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations

arXiv:2603. 06576v2 Announce Type: replace-cross Abstract: The integration of Large Language Models (LLMs) into autonomous driving has attracted growing interest for their strong reasoning and semantic understanding abilities, which are essential for handling complex decision-making and long-tail scenarios.

By Thomas Monninger, Shaoyuan Xie, Qi Alfred Chen, Sihao Ding
arXiv AI
Sep 7

Post Fusion Bird's Eye View Feature Stabilization for Robust Multimodal 3D Detection

The paper introduces Post Fusion Stabilizer (PFS), a lightweight module that refines intermediate bird’s‑eye view (BEV) feature maps in existing camera‑LiDAR fusion detectors. PFS stabilizes feature statistics under domain shift, suppresses regions affected by sensor degradation, and adaptively restores weakened cues via residual correction, acting as a near‑identity transformation. On the nuScenes benchmark, PFS achieves state‑of‑the‑art robustness, notably improving camera dropout robustness by +1.2% and low‑light performance by +4.4% mAP while adding only 3.3 M parameters.

By Trung Tien Dong, Dev Thakkar, Arman Sargolzaei, Xiaomin Lin