@inproceedings{9a11ca8889534d308e4756190465dde2,
title = "DeepFake-o-meter: An Open Platform for DeepFake Detection",
abstract = "In recent years, the advent of deep learning-based techniques and the significant reduction in the cost of computation resulted in the feasibility of creating realistic videos of human faces, commonly known as DeepFakes. The availability of open-source tools to create DeepFakes poses as a threat to the trustworthiness of the online media. In this work, we develop an open-source online platform, known as DeepFake-o-meter, that integrates state-of-The-Art DeepFake detection methods and provide a convenient interface for the users. We describe the design and function of DeepFake-o-meter in this work.",
keywords = "DeepFake Detection, Multimedia Forensics, Software Engineering",
author = "Yuezun Li and Cong Zhang and Pu Sun and Lipeng Ke and Yan Ju and Honggang Qi and Siwei Lyu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Symposium on Security and Privacy Workshops, SPW 2021 ; Conference date: 27-05-2021 Through 27-05-2021",
year = "2021",
month = may,
doi = "10.1109/SPW53761.2021.00047",
language = "English",
series = "Proceedings - 2021 IEEE Symposium on Security and Privacy Workshops, SPW 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "277--281",
booktitle = "Proceedings - 2021 IEEE Symposium on Security and Privacy Workshops, SPW 2021",
address = "United States",
}