The attached gif videos (inference_result_1 and inference_result_2) showcase qualitative results with yellow boxes representing detected objects using ASF (camera + LiDAR + 4D Radar). From left to right, the videos depict: (1) front-facing camera images, (2) LiDAR point clouds, (3) 4D Radar tensors, and (4) sensor attention maps (SAMs).

ASF stands out with three key advantages:
1. sensor availability awareness, which maintains performance even when sensors fail or degrade in adverse conditions by automatically prioritizing available sensors (The SAMs show red, green, and blue representing attention scores for Camera, LiDAR, and 4D Radar respectively, with predominantly blue SAMs in adverse weather indicating that 4D Radar automatically received the highest attention);
2. efficient computation structure with minimal memory usage (1.5-1.6GB) and high processing speeds (13.5-20.5Hz);
3. superior detection performance (87.4% AP3D at IoU=0.3 and 73.6% AP3D at IoU=0.5) even under challenging weather conditions.