3 papers
cs.CV2026
Reconstruction Matters: Learning Geometry-Aligned BEV Representation through 3D Gaussian Splatting
Yiren Lu, Xin Ye, Burhaneddin Yaman +4
Bird's-Eye-View (BEV) perception serves as a cornerstone for autonomous driving, offering a unified spatial representation that fuses surrounding-view images to enable reasoning fo…
cs.RO2025
LTDA-Drive: LLMs-guided Generative Models based Long-tail Data Augmentation for Autonomous Driving
Mahmut Yurt, Xin Ye, Yunsheng Ma +5
3D perception plays an essential role for improving the safety and performance of autonomous driving. Yet, existing models trained on real-world datasets, which naturally exhibit l…
cs.CV2025
ALN-P3: Unified Language Alignment for Perception, Prediction, and Planning in Autonomous Driving
Yunsheng Ma, Burhaneddin Yaman, Xin Ye +5
Recent advances have explored integrating large language models (LLMs) into end-to-end autonomous driving systems to enhance generalization and interpretability. However, most exis…