# SimuFreeMark: A Noise-Simulation-Free Robust Watermarking Against Image Editing

arXiv: https://arxiv.org/abs/2511.11295 · HTML: https://mlsanity.com/paper/2511.11295/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 33 references that are in the map.
- First posted on arXiv 14 Nov 2025.

## Builds on (most cited first, 17 of 17)

- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [InstructPix2Pix: Learning to Follow Image Editing Instructions](https://mlsanity.com/paper/2211.09800/) (2022)
- [Resolution-robust Large Mask Inpainting with Fourier Convolutions](https://mlsanity.com/paper/2109.07161/) (2021)
- [Self-Normalizing Neural Networks](https://mlsanity.com/paper/1706.02515/) (2017)
- [HiDDeN: Hiding Data With Deep Networks](https://mlsanity.com/paper/1807.09937/) (2018)
- [UltraEdit: Instruction-based Fine-Grained Image Editing at Scale](https://mlsanity.com/paper/2407.05282/) (2024)
- [EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection](https://mlsanity.com/paper/2312.08883/) (2023)
- [MBRS : Enhancing Robustness of DNN-based Watermarking by Mini-Batch of Real and Simulated JPEG Compression](https://mlsanity.com/paper/2108.08211/) (2021)
- [Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances](https://mlsanity.com/paper/2410.18775/) (2024)
- [Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms](https://mlsanity.com/paper/2212.12678/) (2022)
- [RoSteALS: Robust Steganography using Autoencoder Latent Space](https://mlsanity.com/paper/2304.03400/) (2023)
- [ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank](https://mlsanity.com/paper/2312.06135/) (2023)
- [Robust-Wide: Robust Watermarking against Instruction-driven Image Editing](https://mlsanity.com/paper/2402.12688/) (2024)
- [Sim-to-Real: An Unsupervised Noise Layer for Screen-Camera Watermarking Robustness](https://mlsanity.com/paper/2504.18906/) (2025)
- [GenPTW: Latent Image Watermarking for Provenance Tracing and Tamper Localization](https://mlsanity.com/paper/2504.19567/) (2025)
- [SpecGuard: Spectral Projection-based Advanced Invisible Watermarking](https://mlsanity.com/paper/2510.07302/) (2025)

## Abstract (arXiv)

The advancement of artificial intelligence generated content (AIGC) has created a pressing need for robust image watermarking that can withstand both conventional signal processing and novel semantic editing attacks. Current deep learning-based methods rely on training with hand-crafted noise simulation layers, which inherently limit their generalization to unforeseen distortions. In this work, we propose SimuFreeMark, a noise-underlinesimulation-underlinefree waterunderlinemarking framework that circumvents this limitation by exploiting the inherent stability of image low-frequency components. We first systematically establish that low-frequency components exhibit significant robustness against a wide range of attacks. Building on this foundation, SimuFreeMark embeds watermarks directly into the deep feature space of the low-frequency components, leveraging a pre-trained variational autoencoder (VAE) to bind the watermark with structurally stable image representations. This design completely eliminates the need for noise simulation during training. Extensive experiments demonstrate that SimuFreeMark outperforms state-of-the-art methods across a wide range of conventional and semantic attacks, while maintaining superior visual quality.