Name
Abstract | ||
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This paper presents a summary of the DeepFake Game Competition (DFGC) 2021
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. 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
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Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IJCB52358.2021.9484387 | 2021 IEEE International Joint Conference on Biometrics (IJCB) |
Keywords | DocType | ISSN |
DeepFake creation,face swaps,DeepFake game competition,DFGC-21 testing dataset,adversarial game,DeepFake detection,realistic face-swaps,DeepFake technology,DFGC 2021 | Conference | 2474-9680 |
ISBN | Citations | PageRank |
978-1-6654-3781-3 | 1 | 0.36 |
References | Authors | |
0 | 23 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo Peng | 1 | 1 | 2.73 |
| Hongxing Fan | 2 | 2 | 1.04 |
| Wei Wang | 3 | 1 | 0.36 |
| Jing Dong | 4 | 1 | 0.36 |
| Yuezun Li | 5 | 65 | 9.77 |
| Siwei Lyu | 6 | 1406 | 135.38 |
| Qi Li | 7 | 54 | 10.18 |
| Zhenan Sun | 8 | 2379 | 139.49 |
| han chen | 9 | 40 | 6.31 |
| Baoying Chen | 10 | 1 | 0.36 |
| Yanjie Hu | 11 | 1 | 0.36 |
| Shenghai Luo | 12 | 1 | 0.36 |
| Junrui Huang | 13 | 1 | 0.36 |
| Yutong Yao | 14 | 1 | 0.36 |
| Boyuan Liu | 15 | 1 | 0.36 |
| Hefei Ling | 16 | 241 | 39.63 |
| Guosheng Zhang | 17 | 3 | 0.79 |
| Zhiliang Xu | 18 | 1 | 1.04 |
| Changtao Miao | 19 | 1 | 2.05 |
| Changlei Lu | 20 | 1 | 0.36 |
| Shan He | 21 | 1 | 0.36 |
| Xiaoyan Wu | 22 | 1 | 0.36 |
| Wanyi Zhuang | 23 | 1 | 0.70 |