Awesome Watermarking Resources Index

Everything we need to know about Watermark COMPLETE LIST

This page serves as an index to curated "Awesome" lists on watermarking techniques in AI, diffusion models, generative AI, and model protection. Below, you'll find brief overviews of each repository, followed by direct links and additional details for easy navigation. These repositories compile research papers, including key survey papers, on intellectual property protection, content traceability, and related topics in deep learning and generative models.

Brief Overviews

1. AwesomeWatermarking: A curated list of research papers on watermarking, steganography, and intellectual property protection. It covers subtopics like text, image, and model watermarking, with notable survey papers such as "A Brief Survey on Deep Learning Based Data Hiding" (2021), "A Comprehensive Review on Digital Image Watermarking" (2021), and "A Survey of Text Watermarking in the Era of Large Language Models" (2024). Organized into sections with links to papers.

2. Awesome-Diffusion-Model-Watermark: Focuses on watermarking for diffusion models, emphasizing AI-generated image protection and traceability. Key resources include papers from 2021–2025, with surveys like "SoK: Watermarking for AI-Generated Content" (2024) and methods like "Tree-Ring Watermarks" (2023). Features yearly categorization, abstracts, and code links for practical use in cryptography and computer vision.

3. Awesome-GenAI-Watermarking: A comprehensive list of watermarking schemes for generative AI models, including "Fingerprint Rooting" techniques. Covers domains like image, audio, and text, with survey papers such as "A Comprehensive Survey on Robust Image Watermarking" (2022), "Copyright Protection in Generative AI" (2024), and "Detecting Multimedia Generated by Large AI Models" (2024). Includes taxonomy, threat models, attacks, and organized sections with code availability.

4. Awesome-Model-Watermarking-And-Fingerprint (Chinese, with key points translated): Compiles papers on IP protection for deep learning models via watermarking and fingerprinting. Survey papers include "Intellectual Property Protection of Deep Neural Network Models Based on Watermarking Technology" (2024), "Research Progress on Deep Neural Network Model Watermarking" (2024), and "Deep Watermarking for Deep Intellectual Property Protection" (2024). Organized into survey, watermark (white-box/black-box), and fingerprint sections, with links to PDFs and code.

Repository Links and Highlights

Explore each repository for full lists of papers, code implementations, and resources:

• AwesomeWatermarking

  • Main Focus: Broad watermarking and steganography papers.
  • Survey Papers: 7+ highlighted, including deep learning-based hiding and LLM-era text watermarking.
  • Notable: Categorized sections (e.g., Text Watermarking, Model Watermarking) with arXiv links.

• Awesome-Diffusion-Model-Watermark

  • Main Focus: Diffusion model-specific watermarking for AI content.
  • Survey Papers: Includes "SoK: Watermarking for AI-Generated Content" and robust fingerprinting methods.
  • Notable: Yearly organization, author details, and code repositories for many entries.

• Awesome-GenAI-Watermarking

  • Main Focus: Watermarking for generative AI across media types.
  • Survey Papers: 6+ surveys on robust watermarking, model protection, and AI-generated content detection.
  • Notable: Detailed taxonomy, security goals, threat models, and sections on attacks and model stealing.

• Awesome-Model-Watermarking-And-Fingerprint

  • Main Focus: IP protection for DL models (watermarking/fingerprinting).
  • Survey Papers: 3+ comprehensive reviews on watermarking methods and trends.
  • Notable: Sections for white-box/black-box watermarks and fingerprints; includes Chinese resources with English translations for key points.

Contributions or updates to these lists are welcome via the respective repositories!