ATDMNet: Multi-Head Agent Attention and Top-k Dynamic Mask for Camouflaged Object Detection

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 10; p. 3001
• Main Authors: Fu, Rui, Li, Yuehui, Chen, Chih-Cheng, Duan, Yile, Yao, Pengjian, Zhou, Kaixin
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 09.05.2025; MDPI
• Subjects: Accuracy; Analysis; camouflaged object detection; Computational linguistics; Computer vision; digital images; feature extraction; Language processing; Localization; Natural language interfaces; Neural networks; self-attention network; Semantics; visualization; China; self-attention network; camouflaged object detection; visualization; feature extraction; digital images

Camouflaged object detection (COD) encounters substantial difficulties owing to the visual resemblance between targets and their environments, together with discrepancies in multiscale representation of features. Current methodologies confront obstacles with feature distraction, modeling far-reachin...