mlsanityData to 7 Oct 2026

DFGC 2021: A DeepFake Game Competition

arXiv 2106.01217 ↗First posted 2 Jun 2021cs.CVcited by 4

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Abstract (arXiv)

This paper presents a summary of the DFGC 2021 competition. DeepFake technology is developing fast, and realistic face-swaps are increasingly deceiving and hard to detect. At the same time, DeepFake detection methods are also improving. There is a two-party game between DeepFake creators and detectors. This competition provides a common platform for benchmarking the adversarial game between current state-of-the-art DeepFake creation and detection methods. In this paper, we present the organization, results and top solutions of this competition and also share our insights obtained during this event. We also release the DFGC-21 testing dataset collected from our participants to further benefit the research community.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 22 of its 27 references that are in the map. First posted on arXiv 2 Jun 2021.

Builds on

22 of 27 references.

References · 22

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  4. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  5. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
  6. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,875
  7. 2021EfficientNetV2: Smaller Models and Faster Trainingcited by 1,127
  8. 2019FaceForensics++: Learning to Detect Manipulated Facial Imagescited by 1,095
  9. 2017VGGFace2: A dataset for recognising faces across pose and agecited by 911
  10. 2019AugMix: A Simple Data Processing Method to Improve Robustness and Uncertaintycited by 897
  11. 2016Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networkscited by 895
  12. 2020First Order Motion Model for Image Animationcited by 698
10 more
  1. 2019Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensicscited by 573
  2. 2018Albumentations: fast and flexible image augmentationscited by 558
  3. 2019Face X-ray for More General Face Forgery Detectioncited by 469
  4. 2019FSGAN: Subject Agnostic Face Swapping and Reenactmentcited by 319
  5. 2018Exposing DeepFake Videos By Detecting Face Warping Artifactscited by 318
  6. 2020DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detectioncited by 251
  7. 2019FaceShifter: Towards High Fidelity And Occlusion Aware Face Swappingcited by 221
  8. 2020The DeepFake Detection Challenge (DFDC) Datasetcited by 125
  9. 2021FaceController: Controllable Attribute Editing for Face in the Wildcited by 22
  10. 2021DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Resultscited by 6

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Cited by year

Citing papers per year: 2022: 4.

4 papers.

  1. 2022ADD 2022: the First Audio Deep Synthesis Detection Challengecited by 94
  2. 2022Causality-Inspired Taxonomy for Explainable Artificial Intelligencecited by 9
  3. 2022Deepfake: Definitions, Performance Metrics and Standards, Datasets and Benchmarks, and a Meta-Reviewcited by 6
  4. 2022DFGC 2022: The Second DeepFake Game Competitioncited by 5