[WACV 2022] Generalized Facial Manipulation Detection with Edge Region Feature Extraction - Dong-Keon Kim and Kwangsu Kim
- 인공지능 융합 연구실
- 조회수1048
- 2022-01-26
Abstract. This paper presents a generalized and robust face manipulation detection method based on the edge region features appearing in images. Most contemporary face synthesis processes include color awkwardness reduction but damage the natural fingerprint in the edge region. In addition, all of these color correction processes do not proceed in the non-face background region. We also observe that the synthesis process does not take into account the natural properties of the image appearing in the time domain. Considering these observations, we propose a facial forensic framework that utilizes pixel-level color features appearing in the edge region of the whole image. Furthermore, our framework includes a 3D-CNN classification model that interprets the extracted color features spatially and temporally. Unlike other existing studies, we conduct authenticity determination by considering all features extracted from multiple frames within one video. Through extensive experiments, including real-world scenarios to evaluate generalized detection ability, we show that our framework outperforms state-of-the-art facial manipulation detection technologies in terms of accuracy and robustness.