Finding the Achilles Heel: Progressive Identification Network for Camouflaged Object Detection

Mu Chun Chou, Hung Jen Chen, Hong Han Shuai

研究成果: Conference contribution同行評審

摘要

Camouflaged object detection (COD) aims to segment objects assimilating into their surroundings. The key challenge for COD is that there are existing high intrinsic similarities between the target object and the background. To solve this challenging problem, we propose the Cascaded Decamouflage Module to progressively improve the prediction map, where each decamouflage module is composed of the region enhancement block and the reverse attention mining block to accurately detect the camouflaged object and obtain complete target objects. In addition, we introduce the classification-based label reweighting to produce the gated label maps as the supervision for assisting the network to capture the most conspicuous region of a camouflaged object and obtain the target object entirely. Extensive experiments on three challenging datasets demonstrate that the proposed model outperforms state-of-the-art methods under different evaluation metrics.

原文English
主出版物標題ICME 2022 - IEEE International Conference on Multimedia and Expo 2022, Proceedings
發行者IEEE Computer Society
ISBN(電子)9781665485630
DOIs
出版狀態Published - 2022
事件2022 IEEE International Conference on Multimedia and Expo, ICME 2022 - Taipei, Taiwan
持續時間: 18 7月 202222 7月 2022

出版系列

名字Proceedings - IEEE International Conference on Multimedia and Expo
2022-July
ISSN(列印)1945-7871
ISSN(電子)1945-788X

Conference

Conference2022 IEEE International Conference on Multimedia and Expo, ICME 2022
國家/地區Taiwan
城市Taipei
期間18/07/2222/07/22

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