YOLO-Anti: YOLO-based counterattack model for unseen congested object detection

Highlights：

• The paper proposes a novel and efficient network framework dedicated to unseen congestion detection.

• An adaptive context module similar to valve control is proposed to obtain contextual information that balances foreground and background features.

• The paper demonstrates that balanced features on multi-level network prediction maps have a prevailing impact on the accuracy of object detection.

• Accurate detection results are realized through the proposed anti-congestion model for flexible regional mapping.