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of Guangdong Polytechnic Normal University","award":["2021SDKYA127"],"award-info":[{"award-number":["2021SDKYA127"]}]},{"name":"Research Project of Guangdong Polytechnic Normal University","award":["2022SDKYA027"],"award-info":[{"award-number":["2022SDKYA027"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Image forgery localization is critical in defending against the malicious manipulation of image content, and is attracting increasing attention worldwide. In this paper, we propose a Dual-domain Fusion Swin Transformer U-Net (DFST-UNet) for image forgery localization. DFST-UNet is built on a U-shaped encoder\u2013decoder architecture. Swin Transformer blocks are integrated into the U-Net architecture to capture long-range context information and perceive forged regions at different scales. Considering the fact that high-frequency forgery information is an essential clue for forgery localization, a dual-stream encoder is proposed to comprehensively expose forgery clues in both the RGB domain and the frequency domain. A novel high-frequency feature extractor module (HFEM) is designed to extract robust high-frequency features. A hierarchical attention fusion module (HAFM) is designed to effectively fuse the dual-domain features. Extensive experimental results demonstrate the superiority of DFST-UNet over the state-of-the-art methods in the task of image forgery localization.<\/jats:p>","DOI":"10.3390\/e27050535","type":"journal-article","created":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T07:34:03Z","timestamp":1747640043000},"page":"535","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["DFST-UNet: Dual-Domain Fusion Swin Transformer U-Net for Image Forgery Localization"],"prefix":"10.3390","volume":"27","author":[{"given":"Jianhua","family":"Yang","sequence":"first","affiliation":[{"name":"School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou 510630, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anjun","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou 510630, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Mai","sequence":"additional","affiliation":[{"name":"School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou 510630, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7129-9153","authenticated-orcid":false,"given":"Yifang","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou 510630, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1566","DOI":"10.1109\/TIFS.2012.2202227","article-title":"Image forgery localization via fine-grained analysis of CFA artifacts","volume":"7","author":"Ferrara","year":"2012","journal-title":"IEEE Trans. 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