计算机科学与探索 ›› 2023, Vol. 17 ›› Issue (1): 1-26.DOI: 10.3778/j.issn.1673-9418.2205035
张璐,芦天亮,杜彦辉
出版日期:
2023-01-01
发布日期:
2023-01-01
ZHANG Lu, LU Tianliang, DU Yanhui
Online:
2023-01-01
Published:
2023-01-01
摘要: 深度伪造(deepfake)技术的非法应用会对社会稳定、个人名誉甚至国家安全造成恶劣影响,因此针对人脸视频的深度伪造检测成为计算机视觉领域中的难点与研究热点。目前该领域的研究建立在传统人脸识别与图像分类技术基础上,通过搭建深度学习网络判别真伪,但存在数据集质量不一、多模态特征如何有效结合、模型泛化能力较差等问题。为进一步促进深度伪造检测技术的发展,对当前各类人脸视频深度伪造算法进行了全面总结,并对已有算法进行了归类、分析、比较。首先,主要介绍人脸视频深度伪造检测数据集;其次,对近三年主要的伪造视频检测方法进行总结,以特征选择为切入点,从空间特征、时空融合特征、生物特征的角度对各项检测技术进行分类整理,并对基于水印与区块链等非主流检测方法进行介绍;然后,从特征选择、迁移学习、模型设计与训练思路等方面介绍了各类检测方法所呈现出的主流趋势;最后,对全文进行总结并对未来技术发展进行展望。
张璐, 芦天亮, 杜彦辉. 人脸视频深度伪造检测方法综述[J]. 计算机科学与探索, 2023, 17(1): 1-26.
ZHANG Lu, LU Tianliang, DU Yanhui. Overview of Facial Deepfake Video Detection Methods[J]. Journal of Frontiers of Computer Science and Technology, 2023, 17(1): 1-26.
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