articleJun 1, 2020Closed access

DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection

Nanyang Technological University

Indexed incrossref

Abstract

We present our on-going effort of constructing a large- scale benchmark for face forgery detection. The first version of this benchmark, DeeperForensics-1.0, represents the largest face forgery detection dataset by far, with 60, 000 videos constituted by a total of 17.6 million frames, 10 times larger than existing datasets of the same kind. Extensive real-world perturbations are applied to obtain a more challenging benchmark of larger scale and higher diversity. All source videos in DeeperForensics-1.0 are carefully collected, and fake videos are generated by a newly proposed end-to-end face swapping framework. The quality of generated videos outperforms those in existing datasets, validated by user studies.…

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541
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Authors

5

Topics & keywords

Keywords
  • Benchmark (surveying)
  • Computer science
  • Face (sociological concept)
  • Set (abstract data type)
  • Scale (ratio)
  • Artificial intelligence
  • Face detection
  • Facial recognition system
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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