{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,27]],"date-time":"2025-07-27T07:26:25Z","timestamp":1753601185254,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031189098"},{"type":"electronic","value":"9783031189104"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-18910-4_40","type":"book-chapter","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:03:53Z","timestamp":1666825433000},"page":"492-508","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Counterfactual Image Enhancement for\u00a0Explanation of\u00a0Face Swap Deepfakes"],"prefix":"10.1007","author":[{"given":"Bo","family":"Peng","sequence":"first","affiliation":[]},{"given":"Siwei","family":"Lyu","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Dong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,27]]},"reference":[{"unstructured":"DeepFakeDetection. https:\/\/ai.googleblog.com\/2019\/09\/contributing-data-to-deepfake-detection.html","key":"40_CR1"},{"unstructured":"DFDC top performer. https:\/\/github.com\/selimsef\/dfdc_deepfake_challenge","key":"40_CR2"},{"unstructured":"FaceSwap. https:\/\/github.com\/MarekKowalski\/FaceSwap","key":"40_CR3"},{"doi-asserted-by":"crossref","unstructured":"Ciftci, U.A., Demir, I., Yin, L.: FakeCatcher: detection of synthetic portrait videos using biological signals. IEEE Trans. Patt. Anal. Mach. Intell. (2020)","key":"40_CR4","DOI":"10.1109\/TPAMI.2020.3009287"},{"unstructured":"Dolhansky, B., et al: The DeepFake detection challenge dataset. arXiv preprint arXiv:2006.07397 (2020)","key":"40_CR5"},{"doi-asserted-by":"crossref","unstructured":"Fong, R., Patrick, M., Vedaldi, A.: Understanding deep networks via extremal perturbations and smooth masks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2950\u20132958 (2019)","key":"40_CR6","DOI":"10.1109\/ICCV.2019.00304"},{"doi-asserted-by":"crossref","unstructured":"Fong, R.C., Vedaldi, A.: Interpretable explanations of black boxes by meaningful perturbation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3429\u20133437 (2017)","key":"40_CR7","DOI":"10.1109\/ICCV.2017.371"},{"unstructured":"He, Y., et al.: ForgeryNet: a versatile benchmark for comprehensive forgery analysis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4360\u20134369","key":"40_CR8"},{"unstructured":"Jiang, L., Li, R., Wu, W., Qian, C., Loy, C.C.: DeeperForensics-1.0: a large-scale dataset for real-world face forgery detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2889\u20132898","key":"40_CR9"},{"unstructured":"Li, L., Bao, J., Yang, H., Chen, D., Wen, F.: FaceShifter: towards high fidelity and occlusion aware face swapping. arXiv preprint arXiv:1912.13457 (2019)","key":"40_CR10"},{"unstructured":"Li, L., et al.: Face X-ray for more general face forgery detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5001\u20135010","key":"40_CR11"},{"doi-asserted-by":"crossref","unstructured":"Li, Y., Chang, M.C., Lyu, S.: In Ictu oculi: exposing AI created fake videos by detecting eye blinking. In: 2018 IEEE International Workshop on Information Forensics and Security (WIFS), pp. 1\u20137. IEEE (2018)","key":"40_CR12","DOI":"10.1109\/WIFS.2018.8630787"},{"unstructured":"Li, Y., Yang, X., Sun, P., Qi, H., Lyu, S.: Celeb-DF: a large-scale challenging dataset for DeepFake forensics. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3207\u20133216","key":"40_CR13"},{"doi-asserted-by":"crossref","unstructured":"Malolan, B., Parekh, A., Kazi, F.: Explainable deep-fake detection using visual interpretability methods. In: 2020 3rd International Conference on Information and Computer Technologies (ICICT), pp. 289\u2013293. IEEE (2020)","key":"40_CR14","DOI":"10.1109\/ICICT50521.2020.00051"},{"unstructured":"Molnar, C.: Interpretable machine learning. Lulu. com (2020)","key":"40_CR15"},{"doi-asserted-by":"crossref","unstructured":"Nguyen, H.H., Fang, F., Yamagishi, J., Echizen, I.: Multi-task learning for detecting and segmenting manipulated facial images and videos. arXiv preprint arXiv:1906.06876 (2019)","key":"40_CR16","DOI":"10.1109\/BTAS46853.2019.9185974"},{"unstructured":"Nirkin, Y., Keller, Y., Hassner, T.: FSGAN: subject agnostic face swapping and reenactment. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 7184\u20137193","key":"40_CR17"},{"doi-asserted-by":"publisher","unstructured":"Peng, B., et al.: DFGC 2021: a DeepFake game competition. In: 2021 IEEE International Joint Conference on Biometrics (IJCB), pp. 1\u20138. https:\/\/doi.org\/10.1109\/IJCB52358.2021.9484387","key":"40_CR18","DOI":"10.1109\/IJCB52358.2021.9484387"},{"doi-asserted-by":"crossref","unstructured":"Peng, B., Fan, H., Wang, W., Dong, J., Lyu, S.: A unified framework for high fidelity face swap and expression reenactment. IEEE Trans. Circ. Syst. Video Technol. 32, 3673\u20133684 (2021)","key":"40_CR19","DOI":"10.1109\/TCSVT.2021.3106047"},{"unstructured":"Pino, S., Carman, M.J., Bestagini, P.: What\u2019s wrong with this video? Comparing explainers for deepfake detection. arXiv preprint arXiv:2105.05902 (2021)","key":"40_CR20"},{"unstructured":"Rossler, A., Cozzolino, D., Verdoliva, L., Riess, C., Thies, J., Nie\u00dfner, M.: FaceForensics++: learning to detect manipulated facial images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1\u201311","key":"40_CR21"},{"unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-CAM: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626","key":"40_CR22"},{"issue":"11","key":"40_CR23","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1038\/s42256-019-0104-6","volume":"1","author":"W Woods","year":"2019","unstructured":"Woods, W., Chen, J., Teuscher, C.: Adversarial explanations for understanding image classification decisions and improved neural network robustness. Nat. Mach. Intell. 1(11), 508\u2013516 (2019)","journal-title":"Nat. Mach. Intell."},{"doi-asserted-by":"crossref","unstructured":"Zi, B., Chang, M., Chen, J., Ma, X., Jiang, Y.G.: WildDeepfake: a challenging real-world dataset for DeepFake detection. In: Proceedings of the 28th ACM International Conference on Multimedia, pp. 2382\u20132390 (2020)","key":"40_CR24","DOI":"10.1145\/3394171.3413769"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18910-4_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:36:48Z","timestamp":1666827408000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18910-4_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031189098","9783031189104"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18910-4_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"27 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/en.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"564","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"233","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"41% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.03","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.35","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}