{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:06:17Z","timestamp":1764842777740,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031431524"},{"type":"electronic","value":"9783031431531"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-43153-1_24","type":"book-chapter","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T21:01:55Z","timestamp":1693861315000},"page":"283-294","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["FEAD-D: Facial Expression Analysis in\u00a0Deepfake Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5033-9617","authenticated-orcid":false,"given":"Michela","family":"Gravina","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9911-1517","authenticated-orcid":false,"given":"Antonio","family":"Galli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Geremia","family":"De Micco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6852-0377","authenticated-orcid":false,"given":"Stefano","family":"Marrone","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8687-6609","authenticated-orcid":false,"given":"Giuseppe","family":"Fiameni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8176-6950","authenticated-orcid":false,"given":"Carlo","family":"Sansone","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,5]]},"reference":[{"key":"24_CR1","unstructured":"Selim seferbekov: Winner of deepfake detection challenge. https:\/\/github.com\/selimsef\/dfdc_deepfake_challenge"},{"key":"24_CR2","doi-asserted-by":"crossref","unstructured":"Agarwal, S., Hu, L., Ng, E., Darrell, T., Li, H., Rohrbach, A.: Watch those words: Video falsification detection using word-conditioned facial motion. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 4710\u20134719 (2023)","DOI":"10.1109\/WACV56688.2023.00469"},{"issue":"5","key":"24_CR3","doi-asserted-by":"publisher","first-page":"20","DOI":"10.4236\/jcc.2021.95003","volume":"9","author":"AM Almars","year":"2021","unstructured":"Almars, A.M.: Deepfakes detection techniques using deep learning: a survey. J. Comput. Commun. 9(5), 20\u201335 (2021)","journal-title":"J. Comput. Commun."},{"key":"24_CR4","doi-asserted-by":"crossref","unstructured":"Bonettini, N., Cannas, E.D., Mandelli, S., Bondi, L., Bestagini, P., Tubaro, S.: Video face manipulation detection through ensemble of CNNs. In: 2020 25th International Conference on Pattern Recognition (icpr), pp. 5012\u20135019. IEEE (2021)","DOI":"10.1109\/ICPR48806.2021.9412711"},{"key":"24_CR5","volume-title":"Joanna Bitton","author":"B Dolhansky","year":"2020","unstructured":"Dolhansky, B.: Joanna Bitton. The deepfake detection challenge dataset, B.P.J.L.R.H.M.W.C.C.F. (2020)"},{"key":"24_CR6","doi-asserted-by":"publisher","unstructured":"Coccomini, D.A., Messina, N., Gennaro, C., Falchi, F.: Combining efficientnet and vision transformers for video deepfake detection. In: Image Analysis and Processing-ICIAP 2022: 21st International Conference, Lecce, Italy, May 23\u201327, 2022, Proceedings, Part III. pp. 219\u2013229. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-031-06433-3_19","DOI":"10.1007\/978-3-031-06433-3_19"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: CVPR, 2009, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"24_CR8","unstructured":"Dumitru, Ian Goodfellow, W.C.Y.B.: Challenges in representation learning: Facial expression recognition challenge (2013)"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Hosler, B., et al.: Do deepfakes feel emotions? a semantic approach to detecting deepfakes via emotional inconsistencies. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 1013\u20131022 (June 2021)","DOI":"10.1109\/CVPRW53098.2021.00112"},{"issue":"3","key":"24_CR10","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.29.3.033013","volume":"29","author":"S Kaur","year":"2020","unstructured":"Kaur, S., Kumar, P., Kumaraguru, P.: Deepfakes: temporal sequential analysis to detect face-swapped video clips using convolutional long short-term memory. J. Electron. Imaging 29(3), 033013 (2020)","journal-title":"J. Electron. Imaging"},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"L\u00f3pez-Gil, J.M., Gil, R., Garc\u00eda, R., et al.: Do deepfakes adequately display emotions? a study on deepfake facial emotion expression. Comput. Intell. Neurosci. 2022 (2022)","DOI":"10.1155\/2022\/1332122"},{"issue":"3","key":"24_CR12","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1177\/1365712718807226","volume":"23","author":"MH Maras","year":"2019","unstructured":"Maras, M.H., Alexandrou, A.: Determining authenticity of video evidence in the age of artificial intelligence and in the wake of deepfake videos. Int. J. Evidence Proof 23(3), 255\u2013262 (2019)","journal-title":"Int. J. Evidence Proof"},{"key":"24_CR13","doi-asserted-by":"crossref","unstructured":"Mittal, T., Bhattacharya, U., Chandra, R., Bera, A., Manocha, D.: Emotions don\u2019t lie: An audio-visual deepfake detection method using affective cues. In: Proceedings of the 28th ACM International Conference on Multimedia, pp. 2823\u20132832 (2020)","DOI":"10.1145\/3394171.3413570"},{"issue":"10","key":"24_CR14","doi-asserted-by":"publisher","first-page":"6111","DOI":"10.1109\/TPAMI.2021.3093446","volume":"44","author":"Y Nirkin","year":"2021","unstructured":"Nirkin, Y., Wolf, L., Keller, Y., Hassner, T.: Deepfake detection based on discrepancies between faces and their context. IEEE Trans. Pattern Anal. Mach. Intell. 44(10), 6111\u20136121 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"24_CR15","unstructured":"Prashnani, E., Goebel, M., Manjunath, B.: Generalizable deepfake detection with phase-based motion analysis. arXiv preprint arXiv:2211.09363 (2022)"},{"key":"24_CR16","doi-asserted-by":"crossref","unstructured":"Rana, M.S., Nobi, M.N., Murali, B., Sung, A.H.: Deepfake detection: A systematic literature review. IEEE Access (2022)","DOI":"10.1109\/ACCESS.2022.3154404"},{"key":"24_CR17","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818\u20132826 (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"24_CR18","doi-asserted-by":"crossref","unstructured":"Westerlund, M.: The emergence of deepfake technology: a review. Technol. Innov. Manage. Rev. 9(11) (2019)","DOI":"10.22215\/timreview\/1282"},{"key":"24_CR19","unstructured":"Wodajo, D., Atnafu, S.: Deepfake video detection using convolutional vision transformer. arXiv preprint arXiv:2102.11126 (2021)"},{"key":"24_CR20","doi-asserted-by":"publisher","unstructured":"Yadav, G., Maheshwari, S., Agarwal, A.: Contrast limited adaptive histogram equalization based enhancement for real time video system. In: 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 2392\u20132397 (2014). https:\/\/doi.org\/10.1109\/ICACCI.2014.6968381","DOI":"10.1109\/ICACCI.2014.6968381"}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Processing \u2013 ICIAP 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43153-1_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T11:36:06Z","timestamp":1710329766000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43153-1_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031431524","9783031431531"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43153-1_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"5 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Udine","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciap2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iciap2023.org\/","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"144","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":"85","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":"7","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":"59% - 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","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","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"https:\/\/iciap2023.org\/satellite-event\/workshops\/","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}