2025/12/13 by Meilin Li, Li, Meilin, Ji Min He +11
Computer Science · #Advanced Steganography and Watermarking Techniques #Hate Speech and Cyberbullying Detection #Generative Adversarial Networks and Image Synthesis
paper · pdf · doi:10.48550/arxiv.2512.12324
The rapid proliferation of Artificial Intelligence Generated Content has precipitated a crisis of trust and urgent regulatory demands. However, existing identification tools suffer from fragmentation and a lack of support for visible compliance marking. To address these gaps, we introduce the UniMark, an open-source, unified framework for multimodal content governance. Our system features a modular unified engine that abstracts complexities across text, image, audio, and video modalities. Crucially, we propose a novel dual-operation strategy, natively supporting both Hidden Watermarking for copyright protection and Visible Marking for regulatory compliance. Furthermore, we establish a standardized evaluation framework with three specialized benchmarks (Image/Video/Audio-Bench) to ensure rigorous performance assessment. This toolkit bridges the gap between advanced algorithms and engineering implementation, fostering a more transparent and secure digital ecosystem.