March 14, 2024, 4:46 a.m. | Chenhao Lin, Jingyi Deng, Pengbin Hu, Chao Shen, Qian Wang, Qi Li

cs.CV updates on

arXiv:2203.02115v2 Announce Type: replace
Abstract: Deepfake detection automatically recognizes the manipulated medias through the analysis of the difference between manipulated and non-altered videos. It is natural to ask which are the top performers among the existing deepfake detection approaches to identify promising research directions and provide practical guidance. Unfortunately, it's difficult to conduct a sound benchmarking comparison of existing detection approaches using the results in the literature because evaluation conditions are inconsistent across studies. Our objective is to establish a …

abstract analysis arxiv benchmarking deepfake detection difference guidance identify natural practical research through type videos

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