Figure 2 | Scientific Reports

Figure 2

From: Enhancing YOLO for occluded vehicle detection with grouped orthogonal attention and dense object repulsion

Figure 2

Overall architecture of YOLO-OVD. It consists of four parts: the GOA-CSP backbone network, the Laplacian Pyramid module, the Laplacian-Guided Feature Fusion network, and the detection head. GOA, which is our proposed grouped orthogonal attention, is integrated in the CSP layer to enhance the feature learning. Laplacian Pyramid Module is used to extract the Laplacian residual. CIoU-RepLoss compels the predicted bounding boxes to maintain a distance from the other ground truth boxes.

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