Gray 채널 분석을 사용한 딥페이크 탐지 성능 비교 연구
A Comparative Study on Deepfake Detection using Gray Channel Analysis
- 발행
- 2021
- 소속·발행
- 서울여자대학교
- 출처
- 국내 KCI
- 원문등록
- 2021-10-12
- 원문
- 원문 보기 ↗
개념
키워드
Deepfake Detection, Grayscale, Gray, Channel, Deep Learning, Deepfake Detection, Grayscale, Gray, Channel, Deep Learning
초록
Recent development of deep learning techniques for image generation has led to straightforward generation of sophisticated deepfakes. However, as a result, privacy violations through deepfakes has also became increased. To solve this issue, a number of techniques for deepfake detection have been proposed, which are mainly focused on RGB channel-based analysis. Although existing studies have suggested the effectiveness of other color model-based analysis (i.e., Grayscale), their effectiveness has not been quantitatively validated yet. Thus, in this paper, we compare the effectiveness of Grayscale channel-based analysis with RGB channel-based analysis in deepfake detection. Based on the selected CNN-based models and deepfake datasets, we measured the performance of each color model-based analysis in terms of accuracy and time. The evaluation results confirmed that Grayscale channel-based analysis performs better than RGB-channel analysis in several cases.