Cross-Attention Based Multi-Sensor Fusion for Robust Object Detection in ADAS: YOLOv12 with Spatiotemporal Calibration and iHOA-Tuned Temporal Fusion Transformer
This paper proposes CAMSF-ADAS, a robust object detection framework for Advanced Driver Assistance Systems that integrates camera, LiDAR, and radar data through spatiotemporal calibration and cross-attention fusion, leveraging YOLOv12 for localization and an Improved Hippopotamus Optimization Algorithm-tuned Temporal Fusion Transformer for enhanced classification.