Deep Template-Based Watermarking

• Published in: IEEE transactions on circuits and systems for video technology Vol. 31; no. 4; pp. 1436 - 1451
• Main Authors: Fang, Han, Chen, Dongdong, Huang, Qidong, Zhang, Jie, Ma, Zehua, Zhang, Weiming, Yu, Nenghai
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; classification network; deep learning; Distortion; Embedding; enhanced-classified network architecture; Feature extraction; human visual system; Machine learning; Neural networks; Resilience; Robustness; Template-based watermarking; Transform coding; Visualization; Watermarking

Traditional watermarking algorithms have been extensively studied. As an important type of watermarking schemes, template-based approaches maintain a very high embedding rate. In such scheme, the message is often represented by some dedicatedly designed templates, and then the message embedding proc...