venus-guangjian/venus-defakerone

Venus-DeFakerOne is a research project from a team publishing under the name GuangJian Team, focused on detecting fake images and pinpointing exactly which parts of an image have been altered. The README describes it as a unified foundation model for FIDL, which stands for fake image detection and localization: a foundation model is a large AI system trained broadly enough to be reused across several related tasks, in this case spotting manipulated or AI-generated images and marking the specific regions that were changed. The project is documented through a technical report, available both as a PDF inside the repository and on arXiv, with an associated listing on Hugging Face. These links point to academic research and a model release rather than a finished consumer product. As of the README's most recent update, the actual code and API are not yet available. The page states plainly that the API is coming soon, and no working release has shipped. This means there is currently nothing here that a developer could install, run, or plug into their own project. The repository mostly functions as a landing page for the research announcement. For anyone wanting to cite the work formally, the README supplies a BibTeX entry crediting the GuangJian Team and pointing to the 2026 arXiv listing. Outside of the citation and the links to the paper and Hugging Face page, the README gives no installation instructions, no dependency list, no usage examples, and no license, so none of that can be summarized here. In short, Venus-DeFakerOne is best understood today as a placeholder for an upcoming fake image detection tool, backed by a real research paper but without a working release yet. Anyone interested should treat it as something to watch for later rather than something to use right now.