# Deep Learning-based Text-in-Image Watermarking

arXiv: https://arxiv.org/abs/2404.13134 · HTML: https://mlsanity.com/paper/2404.13134/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Placed in Watermarking generated content and models, one of 12 directions in LLM safety and security.
- Builds on 11 of its 19 references that are in the map.
- First posted on arXiv 19 Apr 2024.

## Placed in

- LLM safety and security / [Watermarking generated content and models](https://mlsanity.com/safety/watermarking-generated-content-and-models/)

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [HiDDeN: Hiding Data With Deep Networks](https://mlsanity.com/paper/1807.09937/) (2018)
- [Multi30K: Multilingual English-German Image Descriptions](https://mlsanity.com/paper/1605.00459/) (2016)
- [MBRS : Enhancing Robustness of DNN-based Watermarking by Mini-Batch of Real and Simulated JPEG Compression](https://mlsanity.com/paper/2108.08211/) (2021)
- [ReDMark: Framework for Residual Diffusion Watermarking on Deep Networks](https://mlsanity.com/paper/1810.07248/) (2018)
- [An Automated and Robust Image Watermarking Scheme Based on Deep Neural Networks](https://mlsanity.com/paper/2007.02460/) (2020)
- [A Robust Document Image Watermarking Scheme using Deep Neural Network](https://mlsanity.com/paper/2202.13067/) (2022)
- [A Deep Learning-based Audio-in-Image Watermarking Scheme](https://mlsanity.com/paper/2110.02436/) (2021)

## Built on by (most cited first, 3 of 3)

- [Text-Guided Image Invariant Feature Learning for Robust Image Watermarking](https://mlsanity.com/paper/2503.13805/) (2025)
- [Steganographic Embeddings as an Effective Data Augmentation](https://mlsanity.com/paper/2502.15245/) (2025)
- [Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection](https://mlsanity.com/paper/2506.02665/) (2025)

## Abstract (arXiv)

In this work, we introduce a novel deep learning-based approach to text-in-image watermarking, a method that embeds and extracts textual information within images to enhance data security and integrity. Leveraging the capabilities of deep learning, specifically through the use of Transformer-based architectures for text processing and Vision Transformers for image feature extraction, our method sets new benchmarks in the domain. The proposed method represents the first application of deep learning in text-in-image watermarking that improves adaptivity, allowing the model to intelligently adjust to specific image characteristics and emerging threats. Through testing and evaluation, our method has demonstrated superior robustness compared to traditional watermarking techniques, achieving enhanced imperceptibility that ensures the watermark remains undetectable across various image contents.