A two-stage YOLOv5 + CUT + EfficientNet pipeline for vehicle class and orientation detection improves weighted mAP from 0.284 to 0.365 on the IEEE BigData 2022 VOD test set.
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A 2-Stage Model for Vehicle Class and Orientation Detection with Photo-Realistic Image Generation
A two-stage YOLOv5 + CUT + EfficientNet pipeline for vehicle class and orientation detection improves weighted mAP from 0.284 to 0.365 on the IEEE BigData 2022 VOD test set.