Official project website for the ICRA 2025 paper "Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection"
BEVFusionx - Enhanced BEVFusion: Camera ✓ LiDAR ✓ RADAR ✓ PyTorch 1-2 ✓ CUDA 11-13 ✓
Hybrid Attention and Convolutional Induction Fusion for LiDAR-Camera BEV perception.
Multi-sensor fusion for autonomous vehicles: camera + LiDAR BEVFusion on nuScenes
3D object detection on LiDAR point clouds using BEVFusion and MMDetection3D. Includes custom patches for spconv 2.x and full compatibility with Python 3.10, PyTorch 2.1.2, and CUDA 11.8 on the nuScenes benchmark.
Tri-modal BEV fusion for autonomous driving — 6 cameras + LiDAR + 5 radars, Qwen2-0.5B (INT4+LoRA) + GRU decoder, evaluated on Bench2Drive.
A CARLA safety agent that uses BEVFusion and Radar-aided tracking to assess collision risk and supervise longitudinal control.
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