Vol 9 Issue 1 April 2022-September 2022
Xuan Hau Nguyen, Thai Son Tran
Abstract: Nowadays, smartphones, camcorders, and security cameras are extensively used in many areas of daily life, such as offices, traffic lights, houses, dormitories, and more. Besides that, video content editing software like Window Movie Maker, Video Editor, Adobe Photoshop, Adobe After Effect, etc., are also widely available. They have many methods for editing video content easily. So, anyone can edit video content at their willing; even edited content contrast with original content. Recently, the rapid development of deep learning-based techniques have created deepfake videos with characters' faces replaced by other faces automatically, such as FakeApp, Faceswap, etc. That leads to "seeing is no longer believing.". Also, an authentic video provides stronger evidence in court. Therefore, video forgery detection proves that video authenticity has become an urgent requirement today.
Keywords: Video forgery detection; Video forensic; Deepfake video detection; Deep learning; convolutional neural network.
Title: Video Forgery Detection: State-of-The-Art Review
Author: Xuan Hau Nguyen, Thai Son Tran
International Journal of Recent Research in Mathematics Computer Science and Information Technology
ISSN 2350-1022
Vol. 9, Issue 1, April 2022 - September 2022
Page No: 1-9
Paper Publications
Website: www.paperpublications.org
Published Date: 10-May-2022