A hybrid 3D Swin Transformer with temporal patch shift and class-masked attention improves radar object detection accuracy on CRUW at lower computational cost.
Practical classification of different moving targets using automotive radar and deep neural networks
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Mask-RadarNet: Enhancing Transformer With Spatial-Temporal Semantic Context for Radar Object Detection in Autonomous Driving
A hybrid 3D Swin Transformer with temporal patch shift and class-masked attention improves radar object detection accuracy on CRUW at lower computational cost.