WatermarkCover ImageWatermarked ImageExtracted WatermarkLPIPS = 0.934 PSNR = 15.93 PSNR = 23.36LPIPS = 0.556 PSNR = 33.12 PSNR = 31.16
–Neural Information Processing Systems
Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further localized to the optimal spatial region for seamless embedding. To enable spatiotemporal fusion of watermark patches across video frames, we develop a 3D wavelet transform-enhanced Mamba architecture with a novel spatiotemporal local scanning strategy, effectively modeling long-range dependencies during watermark embedding and retrieval. To the best of our knowledge, this is the first attempt to apply state space models to watermarking, opening new avenues for efficient and robust watermark protection. Extensive experiments demonstrate that Safe-Sora achieves state-of-the-art performance in terms of video quality, watermark fidelity, and robustness, which is largely attributed to our proposals.
Neural Information Processing Systems
Jun-23-2026, 00:36:16 GMT
- Country:
- Asia (0.46)
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- Experimental Study (1.00)
- Research Report
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- Information Technology > Security & Privacy (1.00)
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- Information Technology
- Sensing and Signal Processing > Image Processing (1.00)
- Security & Privacy (1.00)
- Data Science (1.00)
- Artificial Intelligence
- Vision (1.00)
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- Machine Learning > Neural Networks (1.00)
- Information Technology