{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T08:15:15Z","timestamp":1783152915885,"version":"3.54.6"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005047","name":"Liaoning Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2025-MSLH-435"],"award-info":[{"award-number":["2025-MSLH-435"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2025M781459"],"award-info":[{"award-number":["2025M781459"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Vision and Image Understanding"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.cviu.2026.104797","type":"journal-article","created":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T07:47:11Z","timestamp":1778572031000},"page":"104797","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Dynamic disentanglement: A contrastive causal framework for deepfake detection"],"prefix":"10.1016","volume":"269","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5029-7461","authenticated-orcid":false,"given":"Hui","family":"Shi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guibin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyu","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cviu.2026.104797_b1","series-title":"Invariant risk minimization","author":"Arjovsky","year":"2019"},{"key":"10.1016\/j.cviu.2026.104797_b2","series-title":"The deepfake detection challenge (DFDC) dataset [dataset]","author":"Dolhansky","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b3","series-title":"International Conference on Learning Representations","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2021"},{"key":"10.1016\/j.cviu.2026.104797_b4","series-title":"International Conference on Machine Learning","first-page":"3247","article-title":"Leveraging frequency analysis for deep fake image recognition","author":"Frank","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b5","series-title":"AAAI Conference on Artificial Intelligence","first-page":"3010","article-title":"Exploring unbiased deepfake detection via token-level shuffling and mixing","author":"Fu","year":"2025"},{"issue":"11","key":"10.1016\/j.cviu.2026.104797_b6","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1038\/s42256-020-00257-z","article-title":"Shortcut learning in deep neural networks","volume":"2","author":"Geirhos","year":"2020","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.cviu.2026.104797_b7","series-title":"Advances in Neural Information Processing Systems","first-page":"2672","article-title":"Generative adversarial networks","author":"Goodfellow","year":"2014"},{"key":"10.1016\/j.cviu.2026.104797_b8","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5039","article-title":"Lips don\u2019t lie: A generalisable and robust approach to face forgery detection","author":"Haliassos","year":"2021"},{"key":"10.1016\/j.cviu.2026.104797_b9","series-title":"Denoising diffusion probabilistic models","author":"Ho","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b10","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5890","article-title":"Implicit identity-driven deepfake face swapping detection","author":"Huang","year":"2023"},{"key":"10.1016\/j.cviu.2026.104797_b11","series-title":"Advances in Neural Information Processing Systems","first-page":"18661","article-title":"Supervised contrastive learning","volume":"vol. 33","author":"Khosla","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b12","series-title":"IEEE\/CVF International Conference on Computer Vision","first-page":"7444","article-title":"SeeABLE: Soft discrepancies and bounded contrastive learning for exposing deepfakes","author":"Larue","year":"2023"},{"key":"10.1016\/j.cviu.2026.104797_b13","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5001","article-title":"Face X-ray for more general face forgery detection","author":"Li","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b14","series-title":"IEEE International Workshop on Information Forensics and Security","article-title":"In ictu oculi: Exposing AI created fake videos by detecting eye blinking","author":"Li","year":"2018"},{"key":"10.1016\/j.cviu.2026.104797_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2020.107616","article-title":"Identification of deep network generated images using disparities in color components","volume":"174","author":"Li","year":"2020","journal-title":"Signal Process."},{"key":"10.1016\/j.cviu.2026.104797_b16","series-title":"Exposing deepfake videos by detecting face warping artifacts","author":"Li","year":"2018"},{"key":"10.1016\/j.cviu.2026.104797_b17","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"4435","article-title":"Celeb-DF: A large-scale challenging dataset for deepfake forensics","author":"Li","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b18","series-title":"ACM International Conference on Multimedia (ACM MM)","first-page":"1478","article-title":"Exploring disentangled content information for face forgery detection","author":"Liang","year":"2022"},{"key":"10.1016\/j.cviu.2026.104797_b19","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"772","article-title":"Spatial-phase shallow learning: Rethinking face forgery detection in frequency domain","author":"Liu","year":"2021"},{"key":"10.1016\/j.cviu.2026.104797_b20","series-title":"IEEE International Conference on Computer Vision (ICCV)","first-page":"3730","article-title":"Deep learning face attributes in the wild","author":"Liu","year":"2015"},{"key":"10.1016\/j.cviu.2026.104797_b21","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"16317","article-title":"Generalizing face forgery detection with high-frequency features","author":"Luo","year":"2021"},{"key":"10.1016\/j.cviu.2026.104797_b22","article-title":"Convolutional neural network framework for deepfake detection: A diffusion-based approach","volume":"240","author":"Pintelas","year":"2025","journal-title":"Comput. Vis. Image UnderstandIng"},{"key":"10.1016\/j.cviu.2026.104797_b23","series-title":"ACM International Conference on Multimedia (ACM MM)","first-page":"4318","article-title":"DeepRhythm: Exposing deepfakes with attentional visual heartbeat rhythms","author":"Qi","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b24","series-title":"European Conference on Computer Vision","first-page":"86","article-title":"Thinking in frequency: Face forgery detection by mining frequency-aware clues","author":"Qian","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b25","series-title":"IEEE\/CVF International Conference on Computer Vision","first-page":"1","article-title":"FaceForensics++: Learning to detect manipulated facial images","author":"R\u00f6ssler","year":"2019"},{"key":"10.1016\/j.cviu.2026.104797_b26","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"18720","article-title":"Detecting deepfakes with self-blended images","author":"Shiohara","year":"2022"},{"key":"10.1016\/j.cviu.2026.104797_b27","series-title":"AAAI Conference on Artificial Intelligence","first-page":"2316","article-title":"Dual contrastive learning for general face forgery detection","author":"Sun","year":"2022"},{"key":"10.1016\/j.cviu.2026.104797_b28","series-title":"International Conference on Machine Learning","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","author":"Tan","year":"2019"},{"key":"10.1016\/j.cviu.2026.104797_b29","series-title":"IEEE International Conference on Multimedia and Expo","article-title":"Illumination enlightened spatial\u2013temporal inconsistency for deepfake video detection","author":"Tian","year":"2024"},{"key":"10.1016\/j.cviu.2026.104797_b30","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"4129","article-title":"AltFreezing for more general video face forgery detection","author":"Wang","year":"2023"},{"key":"10.1016\/j.cviu.2026.104797_b31","series-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"8695","article-title":"CNN-generated images are surprisingly easy to spot\u2026 for now","author":"Wang","year":"2020"},{"key":"10.1016\/j.cviu.2026.104797_b32","series-title":"IEEE\/CVF International Conference on Computer Vision","first-page":"22305","article-title":"UCF: Uncovering common features for generalizable deepfake detection","author":"Yan","year":"2023"},{"key":"10.1016\/j.cviu.2026.104797_b33","series-title":"IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"8261","article-title":"Exposing deep fakes using inconsistent head poses","author":"Yang","year":"2019"},{"key":"10.1016\/j.cviu.2026.104797_b34","series-title":"Pattern Recognition and Computer Vision","first-page":"231","article-title":"Mining temporal inconsistency with 3D face model for deepfake video detection","author":"Yu","year":"2023"},{"issue":"4","key":"10.1016\/j.cviu.2026.104797_b35","doi-asserted-by":"crossref","first-page":"12479","DOI":"10.1109\/TCE.2025.3624764","article-title":"Leveraging spatial\u2013temporal illumination features and convolution-transformer hybrid networks for deepfake video detection","volume":"71","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.cviu.2026.104797_b36","series-title":"IEEE\/CVF International Conference on Computer Vision","first-page":"15023","article-title":"Learning self-consistency for deepfake detection","author":"Zhao","year":"2021"}],"container-title":["Computer Vision and Image Understanding"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1077314226001645?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1077314226001645?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T07:17:22Z","timestamp":1783149442000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1077314226001645"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":36,"alternative-id":["S1077314226001645"],"URL":"https:\/\/doi.org\/10.1016\/j.cviu.2026.104797","relation":{},"ISSN":["1077-3142"],"issn-type":[{"value":"1077-3142","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dynamic disentanglement: A contrastive causal framework for deepfake detection","name":"articletitle","label":"Article Title"},{"value":"Computer Vision and Image Understanding","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cviu.2026.104797","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104797"}}