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New survey details deepfake generation and detection methods

By PulseAugur Editorial · [1 sources] ·

Researchers have published a comprehensive survey on deepfake media generation and detection techniques, covering image, video, audio, and multimodal content. The paper categorizes various deepfake types and outlines methods for both creation and detection. It also presents updated rankings of deepfake detectors on popular datasets and introduces a new multimodal benchmark designed to test detector generalization on unseen generated content. Findings suggest that current state-of-the-art detectors struggle to perform effectively on deepfakes produced by novel generation methods. AI

IMPACT Provides a structured overview of deepfake technologies, aiding researchers and developers in understanding current capabilities and challenges in detection.

RANK_REASON Academic paper detailing a survey of a technical field. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New survey details deepfake generation and detection methods

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Academic paper detailing a survey of a technical field. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Florinel-Alin Croitoru, Andrei-Iulian Hiji, Vlad Hondru, Nicolae Catalin Ristea, Paul Irofti, Marius Popescu, Cristian Rusu, Radu Tudor Ionescu, Fahad Shahbaz Khan, Mubarak Shah ·

    Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook

    arXiv:2411.19537v2 Announce Type: replace-cross Abstract: We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and construct taxonomies of deepfake generation …

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