Name
Title | ||
|---|---|---|
Dual-Domain Generative Adversarial Network for Digital Image Operation Anti-Forensics |
Abstract | ||
|---|---|---|
In this letter, we propose a general digital image operation anti-forensic framework based on generative adversarial nets (GANs), called dual-domain generative adversarial network (DDGAN). To tackle the issue of image operation detection, the proposed framework incorporates both operation specific forensic features and machine-learned knowledge to ensure that the generated images exhibit better un... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCSVT.2021.3068294 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | DocType | Volume |
Forensics,Feature extraction,Image coding,Generators,Transform coding,Training,Detectors | Journal | 32 |
Issue | ISSN | Citations |
3 | 1051-8215 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao Xie | 1 | 1 | 1.37 |
| Jiangqun Ni | 2 | 453 | 34.31 |
| Yun Q. Shi | 3 | 2918 | 199.53 |