Beyond Direct Embedding: Secure Separable Latent Space Watermarking for Anti-Screen-Shooting

Existing anti-screen-shooting watermarking methods embed watermarks on either the server or client side. Server-side embedding incurs high computational and communication overhead under concurrent requests, while client-side methods risk watermark interception during transmission and require additional encrypted channels. To address these limitations, we propose an end-to-end separable watermarking framework (SepWater) that exploits latent space representations. By decoupling server-side watermark embedding from client-side image generation, SepWater enhances security by preventing leaks of both the original content and the watermark, while also reducing transmission costs. On the server side, a dedicated encoder processes the watermark information, while a frozen pre-trained encoder handles the original image. We then fuse their outputs into a compact latent vector for transmission to the client. On the client side, a frozen VQGAN decoder reconstructs the watermarked image directly. In addition, we propose a local residual attention loss, combined with other image quality constraints, to produce watermarked images with high capture resistance and visual fidelity. Furthermore, to improve the robustness of the SepWater, two noise modes are simulated that contain eye protection noise and lightweight edge grayscale deviation noise. Experiments show that SepWater outperforms state-of-the-art methods in withstanding screen-shooting distortions, optimizing communication efficiency, and scaling under high concurrency, making it suitable for practical deployment. The source code is released at https://github.com/CVhnu/SepWater.