Name
Abstract | ||
|---|---|---|
Benefitting from the development of deep generative networks, modern fake news generation methods called Deepfake rapidly go viral over the Internet, calling for efficient detection methods. Existing Deepfake detection methods basically use binary classification networks trained on frame-level inputs and lack leveraging temporal information in videos. Besides, the accuracy of these methods will ra... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TBIOM.2021.3065735 | IEEE Transactions on Biometrics, Behavior, and Identity Science |
Keywords | DocType | Volume |
Videos,Information integrity,Faces,Forgery,Feature extraction,Splicing,Biometrics (access control) | Journal | 3 |
Issue | Citations | PageRank |
3 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bing Han | 1 | 36 | 11.27 |
| Xiaoguang Han | 2 | 220 | 29.01 |
| Hua Zhang | 3 | 1 | 0.35 |
| Jingzhi Li | 4 | 2 | 1.37 |
| Xiaochun Cao | 5 | 1986 | 131.55 |