{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/busternet-detecting-copy-move-image-forgery","title":"BusterNet: Detecting Copy-Move Image Forgery with Source/Target Localization","arxiv_id":null,"date":"2018-09-01","proceeding":"ECCV 2018 9","authors":["Yue Wu","Wael Abd-Almageed","Prem Natarajan"],"abstract":"We introduce a novel deep neural architecture for image copy-move forgery detection (CMFD), code-named BusterNet. Unlike previous eorts, BusterNet is a pure, end-to-end trainable, deep neural network solution. It features a two-branch architecture followed by a fu- sion module. The two branches localize potential manipulation regions (by looking for visual artifacts) and copy-move regions (by assessing vi- sual similarities), respectively. To the best of our knowledge, this is the rst CMFD algorithm with discernibility to localize source/target re- gions.We also propose simple schemes for synthesizing large-scale CMFD samples using out-of-domain datasets, and stage-wise strategies for eec- tive BusterNet training. Our extensive studies demonstrate that Buster- Net outperforms state-of-the-art copy-move detection algorithms by a large margin on the two publicly available datasets, CASIA and CoMo- FoD, and that it is robust against various known attacks.","url_abs":"http://openaccess.thecvf.com/content_ECCV_2018/html/Rex_Yue_Wu_BusterNet_Detecting_Copy-Move_ECCV_2018_paper.html","url_pdf":"http://openaccess.thecvf.com/content_ECCV_2018/papers/Rex_Yue_Wu_BusterNet_Detecting_Copy-Move_ECCV_2018_paper.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"busternet-detecting-copy-move-image-forgery","repo_url":"https://github.com/isi-vista/BusterNet","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}