# End-to-end Trained CNN Encode-Decoder Networks for Image Steganography

arXiv: https://arxiv.org/abs/1711.07201 · HTML: https://mlsanity.com/paper/1711.07201/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Nov 2017.

## Built on by (most cited first, 18 of 18)

- [Exploiting Explanations for Model Inversion Attacks](https://mlsanity.com/paper/2104.12669/) (2021)
- [Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography](https://mlsanity.com/paper/2107.09287/) (2021)
- [Learning to Immunize Images for Tamper Localization and Self-Recovery](https://mlsanity.com/paper/2210.15902/) (2022)
- [PrObeD: Proactive Object Detection Wrapper](https://mlsanity.com/paper/2310.18788/) (2023)
- [Multi-Stage Residual Hiding for Image-into-Audio Steganography](https://mlsanity.com/paper/2101.01872/) (2021)
- [Information hiding cameras: optical concealment of object information into ordinary images](https://mlsanity.com/paper/2401.07856/) (2024)
- [A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures](https://mlsanity.com/paper/2404.00673/) (2024)
- [Learning Iterative Neural Optimizers for Image Steganography](https://mlsanity.com/paper/2303.16206/) (2023)
- [Hiding Images into Images with Real-world Robustness](https://mlsanity.com/paper/2110.05689/) (2021)
- [Multitask Identity-Aware Image Steganography via Minimax Optimization](https://mlsanity.com/paper/2107.05819/) (2021)
- [Towards Robust Image-in-Audio Deep Steganography](https://mlsanity.com/paper/2303.05007/) (2023)
- [Cover-separable Fixed Neural Network Steganography via Deep Generative Models](https://mlsanity.com/paper/2407.11405/) (2024)
- [SMILENet: Unleashing Extra-Large Capacity Image Steganography via a Synergistic Mosaic InvertibLE Hiding Network](https://mlsanity.com/paper/2503.05118/) (2025)
- [Deniable Steganography](https://mlsanity.com/paper/2205.12587/) (2022)
- [ESDiff: Encoding Strategy-inspired Diffusion Model with Few-shot Learning for Color Image Inpainting](https://mlsanity.com/paper/2504.17524/) (2025)
- [README: Robust Error-Aware Digital Signature Framework via Deep Watermarking Model](https://mlsanity.com/paper/2507.04495/) (2025)
- [Breaking the Resolution Barrier: Arbitrary-resolution Deep Image Steganography Framework](https://mlsanity.com/paper/2601.15739/) (2026)
- [StegGNN: Learning Graphical Representation for Image Steganography](https://mlsanity.com/paper/2609.32362/) (2026)

## Abstract (arXiv)

All the existing image steganography methods use manually crafted features to hide binary payloads into cover images. This leads to small payload capacity and image distortion. Here we propose a convolutional neural network based encoder-decoder architecture for embedding of images as payload. To this end, we make following three major contributions: (i) we propose a deep learning based generic encoder-decoder architecture for image steganography; (ii) we introduce a new loss function that ensures joint end-to-end training of encoder-decoder networks; (iii) we perform extensive empirical evaluation of proposed architecture on a range of challenging publicly available datasets (MNIST, CIFAR10, PASCAL-VOC12, ImageNet, LFW) and report state-of-the-art payload capacity at high PSNR and SSIM values.