mlsanityData to 7 Oct 2026

1M-Deepfakes Detection Challenge

arXiv 2409.06991 ↗First posted 11 Sep 2024cs.CVcited by 4

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Abstract (arXiv)

The detection and localization of deepfake content, particularly when small fake segments are seamlessly mixed with real videos, remains a significant challenge in the field of digital media security. Based on the recently released AV-Deepfake1M dataset, which contains more than 1 million manipulated videos across more than 2,000 subjects, we introduce the 1M-Deepfakes Detection Challenge. This challenge is designed to engage the research community in developing advanced methods for detecting and localizing deepfake manipulations within the large-scale high-realistic audio-visual dataset. The participants can access the AV-Deepfake1M dataset and are required to submit their inference results for evaluation across the metrics for detection or localization tasks. The methodologies developed through the challenge will contribute to the development of next-generation deepfake detection and localization systems. Evaluation scripts, baseline models, and accompanying code will be available on https://github.com/ControlNet/AV-Deepfake1M.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 33 of its 57 references that are in the map. First posted on arXiv 11 Sep 2024.

Builds on

33 of 57 references.

References · 33

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  11. 2020Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detectioncited by 286
  12. 2020DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detectioncited by 251
21 more
  1. 2022Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformercited by 244
  2. 2018DeepFakes: a New Threat to Face Recognition? Assessment and Detectioncited by 208
  3. 2021WildDeepfake: A Challenging Real-World Dataset for Deepfake Detectioncited by 207
  4. 2021FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Datasetcited by 179
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  6. 2021ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysiscited by 124
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  9. 2022ADD 2022: the First Audio Deep Synthesis Detection Challengecited by 94
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  11. 2021Face Forensics in the Wildcited by 87
  12. 2023Self-Supervised Video Forensics by Audio-Visual Anomaly Detectioncited by 84
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  14. 2024AVFF: Audio-Visual Feature Fusion for Video Deepfake Detectioncited by 59
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  17. 2021OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wildcited by 50
  18. 2023Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localizationcited by 42
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  21. 2024Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysiscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025AV-Deepfake1M++: A Large-Scale Audio-Visual Deepfake Benchmark with Real-World Perturbationscited by 8
  2. 2026ActivityForensics: A Comprehensive Benchmark for Localizing Manipulated Activity in Videoscited by 1
  3. 2025Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systemscited by 0
  4. 2026A General Model for Deepfake Speech Detection: Diverse Bonafide Resources or Diverse AI-Based Generatorscited by 0