mlsanityData to 14 Oct 2026

DFGC 2022: The Second DeepFake Game Competition

arXiv 2206.15138 ↗First posted 30 Jun 2022cs.CVcited by 5

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Abstract (arXiv)

This paper presents the summary report on our DFGC 2022 competition. The DeepFake is rapidly evolving, and realistic face-swaps are becoming more deceptive and difficult to detect. On the contrary, methods for detecting DeepFakes are also improving. There is a two-party game between DeepFake creators and defenders. This competition provides a common platform for benchmarking the game between the current state-of-the-arts in DeepFake creation and detection methods. The main research question to be answered by this competition is the current state of the two adversaries when competed with each other. This is the second edition after the last year's DFGC 2021, with a new, more diverse video dataset, a more realistic game setting, and more reasonable evaluation metrics. With this competition, we aim to stimulate research ideas for building better defenses against the DeepFake threats. We also release our DFGC 2022 dataset contributed by both our participants and ourselves to enrich the DeepFake data resources for the research community (https://github.com/NiCE-X/DFGC-2022).

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 29 of its 39 references that are in the map. First posted on arXiv 30 Jun 2022.

Builds on

29 of 39 references.

References · 29

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17 more
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Cited by year

Citing papers per year: 2023: 3; 2024: 1; 2025: 1.

5 papers.

  1. 2024Social Media Authentication and Combating Deepfakes using Semi-fragile Invisible Image Watermarkingcited by 6
  2. 2023Visual Realism Assessment for Face-swap Videoscited by 3
  3. 2023Fooling State-of-the-Art Deepfake Detection with High-Quality Deepfakescited by 3
  4. 2023Beyond Detection: Visual Realism Assessment of Deepfakescited by 0
  5. 2025DREAM: A Benchmark Study for Deepfake photoREalism AssessMentcited by 0