{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T17:36:36Z","timestamp":1784136996614,"version":"3.55.0"},"reference-count":58,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T00:00:00Z","timestamp":1664323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Multimedia data manipulation and forgery has never been easier than today, thanks to the power of Artificial Intelligence (AI). AI-generated fake content, commonly called Deepfakes, have been raising new issues and concerns, but also new challenges for the research community. The Deepfake detection task has become widely addressed, but unfortunately, approaches in the literature suffer from generalization issues. In this paper, the Face Deepfake Detection and Reconstruction Challenge is described. Two different tasks were proposed to the participants: (i) creating a Deepfake detector capable of working in an \u201cin the wild\u201d scenario; (ii) creating a method capable of reconstructing original images from Deepfakes. Real images from CelebA and FFHQ and Deepfake images created by StarGAN, StarGAN-v2, StyleGAN, StyleGAN2, AttGAN and GDWCT were collected for the competition. The winning teams were chosen with respect to the highest classification accuracy value (Task I) and \u201cminimum average distance to Manhattan\u201d (Task II). Deep Learning algorithms, particularly those based on the EfficientNet architecture, achieved the best results in Task I. No winners were proclaimed for Task II. A detailed discussion of teams\u2019 proposed methods with corresponding ranking is presented in this paper.<\/jats:p>","DOI":"10.3390\/jimaging8100263","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T22:53:19Z","timestamp":1664405599000},"page":"263","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["The Face Deepfake Detection Challenge"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8315-351X","authenticated-orcid":false,"given":"Luca","family":"Guarnera","sequence":"first","affiliation":[{"name":"Department of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8343-2049","authenticated-orcid":false,"given":"Oliver","family":"Giudice","sequence":"additional","affiliation":[{"name":"Applied Research Team, IT Department, Banca d\u2019Italia, 00044 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7703-3367","authenticated-orcid":false,"given":"Francesco","family":"Guarnera","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3461-4679","authenticated-orcid":false,"given":"Alessandro","family":"Ortis","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6222-9933","authenticated-orcid":false,"given":"Giovanni","family":"Puglisi","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, University of Cagliari, 09124 Cagliari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0883-147X","authenticated-orcid":false,"given":"Antonino","family":"Paratore","sequence":"additional","affiliation":[{"name":"iCTLab s.r.l., 95125 Catania, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4049-2156","authenticated-orcid":false,"given":"Linh M. 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