Watermark Any Image: A Unified Framework

Embedding data in images while maintaining visual quality and ensuring reliable detection and decoding remains a challenge in image watermarking. We introduce UniMark, a unified watermark framework for zero-bit detection, multi-bit detection, and multi-bit decoding that operates directly on existing images without accessing or modifying the generator. UniMark calibrates projection scores in reconstructable image representations using unwatermarked distributions and modifies these scores to embed watermark information. We develop statistical watermark constructions and corresponding likelihood-ratio tests for detection and decoding. These tests are optimal under independence, while finite-sample analysis demonstrates near-optimal performance. Experiments on three real-image datasets and images from four generative models demonstrate high image fidelity at near-perfect detection rates across diverse image sources. UniMark supports payloads of up to 32,768 bits, twice the largest payload of the existing largest payload watermark method, and achieves a 92% full-message recovery rate at 8,192 bits under clean conditions, which existing methods have not demonstrated. Our anonymous code repository is available at [this anonymous repository](https://anonymous.4open.science/r/WatermarkyAnyImage-UniMark-58C5).