A Serial Image Copy-Move Forgery Localization Scheme With Source/Target Distinguishment

• Published in: IEEE transactions on multimedia Vol. 23; pp. 3506 - 3517
• Main Authors: Chen, Beijing, Tan, Weijin, Coatrieux, Gouenou, Zheng, Yuhui, Shi, Yun-Qing
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; atrous convolution; attention mechanism; Convolution; Copy-move; Correlation; Datasets; Decoding; deep neural network; Feature extraction; Forgery; image forgery; Localization; Similarity; Target detection; Task analysis

In this paper, we improve the parallel deep neural network (DNN) scheme BusterNet for image copy-move forgery localization with source/target region distinguishment. BusterNet is based on two branches, i.e., Simi-Det and Mani-Det, and suffers from two main drawbacks: (a) it should ensure that both b...