What is it about?
This study is about Deepfake Video Detection based on Audio Visual information in the video. We are primarily targeting the synchronization between audio and video modality to spot Deepfake videos. The proposed model is based on Deep Learning.
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Why is it important?
Due to the rise in manipulated and fake videos, we need automated methods to timely detect and spot deepfake videos and avoid their spread on social media. Deepfakes can be used in many forms, among which spreading false political propaganda, generating fake adult videos, synthesizing Deepfake calls, generating fake news, stealing identities for financial gain, and slandering others have recently become common.
Perspectives
The audio-visual or multimodal aspect of Deepfake videos/content is less explored, it needs more attention from the Multimedia research forensics community to collaborate and propose new methods to address this challenging issue.
Adil Shahzad
Academia Sinica
Read the Original
This page is a summary of: Lip Sync Matters: A Novel Multimodal Forgery Detector, November 2022, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.23919/apsipaasc55919.2022.9980296.
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