2024/11/29 by Florinel-Alin Croitoru, Croitoru, Florinel-Alin, Andrei-Iulian Hiji +17 · 4 citations
Computer Science · Engineering · Psychology · #Artificial intelligence #Computer science #Data science #Digital Media Forensic Detection #Engineering #Engineering ethics #Epistemology #Generative Adversarial Networks and Image Synthesis #Generative grammar #Philosophy #Political science #Psychology #cs.AI #cs.CV #cs.LG #cs.MM #cs.SD #eess.AS
paper · pdf · open access · doi:10.1145/3833867
published in ACM Computing Surveys (Association for Computing Machinery) · Accepted in ACM Computing Surveys
openalex created_date 2025/10/10 · openalex publication_date 2026/07/23 · arxiv created 2026/07/31 · arxiv updated 2026/08/03 · openalex updated_date 2026/08/04
We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and construct taxonomies of deepfake generation and detection methods, illustrating the important groups of methods. Next, we gather datasets used for deepfake detection and provide updated rankings of the best performing detectors on the most popular datasets. In addition, we develop a novel multimodal benchmark to evaluate deepfake detectors on out-of-distribution content. The results indicate that state-of-the-art detectors fail to generalize to deepfakes generated by unseen generators. Our project page and new benchmark are available at https://github.com/CroitoruAlin/biodeep.