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MFAN: Multi-Level Features Attention Network for Fake Certificate Image Detection

Yu Sun, Rongrong Ni, Yao Zhao
2022 Entropy  
To expand the application of image forensics technology, forgery detection for certificate images that can directly represent people's rights and interests is investigated in this paper.  ...  Furthermore, the resulting multi-level features are recalibrated on channels for irrelevant information suppression and enhancing the tampered regions, guiding the MFAN to adapt to diverse manipulation  ...  To achieve good performance for face forgery detection, PRRNet [37] took advantage of the spatial attention mechanism to learn more competitive features on manipulated regions and the original regions  ... 
doi:10.3390/e24010118 pmid:35052144 pmcid:PMC8774785 fatcat:ud7y3632rne47idcenwdohi564