A continual deepfake detection benchmark: Dataset, methods, and essentials

• Main Authors: LI, Chuqiao, HUANG, Zhiwu, PAUDEL, Danda Pani, WANG, Yabin, SHAHBAZI, Mohamad, HONG, Xiaopeng, VAN GOOL Luc
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: continual deepfake detection; benchmark; incremental learning methods; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7613; https://ink.library.smu.edu.sg/context/sis_research/article/8616/viewcontent/01_CDDB_WACV2023.pdf
• Institution: Singapore Management University

There have been emerging a number of benchmarks and techniques for the detection of deepfakes. However, very few works study the detection of incrementally appearing deepfakes in the real-world scenarios. To simulate the wild scenes, this paper suggests a continual deepfake detection benchmark (CDDB...