Crowdsourced judgments reliably flag authentic videos but frequently miss manipulations and struggle to identify whether changes are audio-only, video-only, or both.
In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’25, pages 457–467, New York, NY, USA
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Beyond Seeing Is Believing: On Crowdsourced Detection of Audiovisual Deepfakes
Crowdsourced judgments reliably flag authentic videos but frequently miss manipulations and struggle to identify whether changes are audio-only, video-only, or both.