Learning Deep Hidng

This repo collects the paper list of Deep Hiding. I have compiled summaries of various papers and organized them into categories. Please feel free to contribute by submitting pull requests!

• [2024/06] StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation
• [2024/03] StegaStyleGAN: Towards Generic and Practical Generative Image Steganography
• [2024] Cross: Diffusion model makes controllable, robust and secure image steganography
• [2023/10] StegaDDPM: Generative Image Steganography based on Denoising Diffusion Probabilistic Model
• [2023] Generative steganography via auto-generation of semantic object contours
• [2023] Secret-to-image reversible transformation for generative steganography
• [2023/08] Robust steganography without embedding based on secure container synthesis and iterative message recovery
• [2017] Generating steganographic images via adversarial training

• [2024/05] Diffusion-Based Hierarchical Image Steganography
• [2024/05] PPRSteg: Printing and Photography Robust QR Code Steganography via Attention Flow-Based Model
• [2024/05] Joint Adaptive Robust Steganography Network
• [2023/04] IRWArt: Levering Watermarking Performance for Protecting High-quality Artwork Images
• [2023/03] Low-frequency image deep steganography: Manipulate the frequency distribution to hide secrets with tenacious robustness
• [2023] Flow-based robust watermarking with invertible noise layer for black-box distortions
• [2023] Flexible and secure watermarking for latent diffusion model
• [2022] Robust invertible image steganography
• [2022] Hiding images into images with real-world robustness
• [2020] High-capacity robust image steganography via adversarial network
• [2019] HidingGAN: High capacity information hiding with generative adversarial network
• [2018] HiDDeN: Hiding data with deep networks

• [2024/06] StampOne: Addressing Frequency Balance in Printer-proof Steganography
• [2024/05] DBDH: A Dual-Branch Dual-Head Neural Network for Invisible Embedded Regions Localization
• [2022] Pimog: An effective screen-shooting noise-layer simulation for deep-learning-based watermarking network
• [2022] Learning invisible markers for hidden codes in offline-to-online photography
• [2021] TERA: Screen-to-camera image code with transparency, efficiency, robustness and adaptability
• [2020] RIHOOP: Robust invisible hyperlinks in offline and online photographs
• [2020] Stegastamp: Invisible hyperlinks in physical photographs
• [2020] UDH: Universal deep hiding for steganography, watermarking, and light field messaging
• [2019] Light field messaging with deep photographic steganography

• [2024/04] Hiding Face Into Background: A Proactive Countermeasure Against Malicious Face Swapping
• [2023/12] Editguard: Versatile image watermarking for tamper localization and copyright protection
• [2021] Fixed neural network steganography: Train the images, not the network
• [2021] Seek-and-hide: adversarial steganography via deep reinforcement learning
• [2021] Multitask identity-aware image steganography via minimax optimization
• [2021] HCISNet: Higher‐capacity invisible image steganographic network

• [2024/04] DHU-Net: High-capacity binary data hiding network based on improved U-Net
• [2024/04] A Keyless Extraction Framework Targeting at Deep Learning Based Image-Within-Image Models
• [2024/03] StegFormer: Rebuilding the Glory of Autoencoder-Based Steganography
• [2024/02] A fitting model with optimal Multiple Image Hiding effect
• [2024/01] Image hiding using invertible neural network and similarity of bits pairs
• [2023] Hiding Multiple Images into a Single Image Using Up-sampling
• [2023] Deep adaptive hiding network for image hiding using attentive frequency extraction and gradual depth extraction
• [2023] AFcIHNet: Attention feature-constrained network for single image information hiding
• [2022] DeepMIH: Deep invertible network for multiple image hiding
• [2021] FCANet: Frequency channel attention networks
• [2021] HiNet: Deep image hiding by invertible network
• [2021] Large-capacity image steganography based on invertible neural networks
• [2021] Channel attention image steganography with generative adversarial networks
• [2021] A data hiding scheme based on U-Net and wavelet transform
• [2020] Attention based data hiding with generative adversarial networks
• [2019] Invisible steganography via generative adversarial networks
• [2019] Hiding images within images
• [2019] Image steganography using texture features and GANs
• [2018] End-to-end trained CNN encoder-decoder networks for image steganography
• [2017] Hiding images in plain sight: Deep steganography

• [2024/04] Image Steganography with Deep Orthogonal Fusion of Multi-Scale Channel Attention
• [2024/03] Conditional image hiding network based on style transfer
• [2024/02] DUIANet: A double layer U-Net image hiding method based on improved Inception module and attention mechanism
• [2024/02] Meta Security Metric Learning for Secure Deep Image Hiding
• [2024/01] Conditional image hiding network based on style transfer
• [2023] Securing Fixed Neural Network Steganography

• [2024/02] Purified and Unified Steganographic Network

• [2024/05] GS-Hider: Hiding Messages into 3D Gaussian Splatting

• [2024/06] StegaNeRV: Video Steganography using Implicit Neural Representation
• [2023] Large-capacity and flexible video steganography via invertible neural network
• [2023] VHNet: A Video Hiding Network with robustness to video coding

• [2023/08] Wavmark: Watermarking for audio generation

• [2023] Invertible Energy-Aware Images

• [2023] Copyrnerf: Protecting the copyright of neural radiance fields
• [2023] Steganerf: Embedding invisible information within neural radiance fields

• [2024/06] Are Deepfakes a Game Changer in Digital Images Steganography Leveraging the Cover-Source-Mismatch?

• [2024] An invisible, robust copyright protection method for DNN-generated content

• [2023] Large-capacity and flexible video steganography via invertible neural network

• [2024] Learning-based image steganography and watermarking: A survey
• [2024] When deep learning meets watermarking: A survey of application, attacks and defenses
• [2022] A comprehensive survey on robust image watermarking
• [2021] A brief survey on deep learning based data hiding