{"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/on-disentangling-spoof-trace-for-generic-face","title":"On Disentangling Spoof Trace for Generic Face Anti-Spoofing","arxiv_id":"2007.09273","date":"2020-07-17","proceeding":"ECCV 2020 8","authors":["Yaojie Liu","Joel Stehouwer","Xiaoming Liu"],"abstract":"Prior studies show that the key to face anti-spoofing lies in the subtle image pattern, termed \"spoof trace\", e.g., color distortion, 3D mask edge, Moire pattern, and many others. Designing a generic anti-spoofing model to estimate those spoof traces can improve not only the generalization of the spoof detection, but also the interpretability of the model's decision. Yet, this is a challenging task due to the diversity of spoof types and the lack of ground truth in spoof traces. This work designs a novel adversarial learning framework to disentangle the spoof traces from input faces as a hierarchical combination of patterns at multiple scales. With the disentangled spoof traces, we unveil the live counterpart of the original spoof face, and further synthesize realistic new spoof faces after a proper geometric correction. Our method demonstrates superior spoof detection performance on both seen and unseen spoof scenarios while providing visually convincing estimation of spoof traces. Code is available at https://github.com/yaojieliu/ECCV20-STDN.","url_abs":"https://arxiv.org/abs/2007.09273v1","url_pdf":"https://arxiv.org/pdf/2007.09273v1.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":"on-disentangling-spoof-trace-for-generic-face","repo_url":"https://github.com/yaojieliu/ECCV20-STDN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"face-anti-spoofing","task_name":"Face Anti-Spoofing"}],"methods":[{"method_slug":"interpretability","method_name":"Interpretability"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2007.09273","atlas_url":"https://app.syntology.ai/?focus=2007.09273","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}