Camouflaged Object Detection via Context-Aware Cross-Level Fusion

• Published in: IEEE transactions on circuits and systems for video technology Vol. 32; no. 10; pp. 6981 - 6993
• Main Authors: Chen, Geng, Liu, Si-Jie, Sun, Yu-Jia, Ji, Ge-Peng, Wu, Ya-Feng, Zhou, Tao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Camouflaged object detection; Computational modeling; Context; context-aware deep learning; Datasets; Deep learning; Feature extraction; feature fusion; Image segmentation; Mathematical models; Modules; Object detection; Object recognition; polyp segmentation; Task analysis

Camouflaged object detection (COD) aims to identify the objects that conceal themselves in natural scenes. Accurate COD suffers from a number of challenges associated with low boundary contrast and the large variation of object appearances, e.g., object size and shape. To address these challenges, w...