关键词: 目标检测, 迷彩伪装, 注意力机制

Abstract:

Camouflage technology can effectively reduce the visual significance of the objects, which conduce a huge challenge to camouflage objects detection. Based on RetinaNet detection framework, spatial attention and channel attention modules are embeded for camouflage features extraction, and a new prediction box filtering algorithm is built based on positioning confidence score, which effectively realizes the detection for camouflage personnel. Experimental results on the extended camouflage dataset show that the average detection accuracy of the proposed model reaches 93.1%, which improves by 8.7 percentage points.

Key words: object detection, camouflage, attention mechanism