Illegal 3D Content Distribution Tracking System based on DNN Forensic Watermarking
Jaehyoung Park, Jihye Kim, Jiyou Seo, Sangpil Kim, Jong‐Hyouk Lee · 2023
With the development of the metaverse industry and the expansion of the 3D content market required to build the metaverse ecosystem, artificial intelligence technology that can create usable 3D content is developing. On the other hand, there is currently no legal definition of copyright for 3D content created based on artificial intelligence, and the scope of copyright application is ambiguous. In the current situation where copyright disputes and infringements on 3D contents are expected, this paper proposes a Deep Neural Network (DNN) forensic watermarking-based illegal 3D content distribution tracking system to protect illegal copying and distribution of 3D content. In this paper, we present our design result for the illegal 3D content distribution tracking system with detailed architecture, components, and message flows.