Strip multi-vendor AI provenance marks: Unicode text hygiene, statistical rewrite hooks, and C2PA/metadata from PNG/JPEG/SVG/PDF/DOCX/HTML/MD
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Updated
Aug 27, 2026 - Python
Strip multi-vendor AI provenance marks: Unicode text hygiene, statistical rewrite hooks, and C2PA/metadata from PNG/JPEG/SVG/PDF/DOCX/HTML/MD
Project for Digital Image Processing
Replace color with another one pixel by pixel.
Model for watermark classification implemented with PyTorch
Local-first, open-source AI watermark removal for Gemini, Doubao, Qwen, Jimeng, Kling, Tencent Yuanbao, Baidu, and more. Smart localization, Gemini reverse-alpha recovery, and LaMa inpainting. Includes a Web UI, CLI, and Python API; supports CUDA, Apple Silicon, and CPU.
claude anti-watermarking
Cross platform CLI tool for removing watermarks from images and videos generated by Google Gemini, Veo, and NotebookLM.
Repository related to the Catch the Mark competition of the Multimedia Data Security graduate course of University of Trento, academic year 2022/2023.
Resilient watermarking of digital images
Test what AI watermark and provenance evidence exists, whether it verifies, and what survives publishing.
Claude Watermark Remover: detect and strip hidden invisible-character watermarks from Claude, ChatGPT, and other LLM-generated text. Free, open-source, runs 100% locally with Next.js + Ollama.
Remove watermark from Sora 2 AI videos for free in one click.
Open-source AI text watermark remover for Unicode artifacts, with detector-scoped evaluation of published statistical LLM watermark schemes.
Reveal or Remove any watermark generated by ai
🕵️ AI content detector and watermark checker. Detect AI-generated text (SynthID, KGW/green-list, Gumbel, Unigram, SWEET) and verify C2PA provenance in images, video, audio, and PDFs. Fast Rust CLI with JSON/XML/YAML output.
A model for watermark detection using Tensorflow.
Audit invisible AI text watermarks and test Claude watermark claims with reproducible, local-first analysis.
Advanced spectral watermarking for 3D models with forensic-level proof of ownership. Invisible, robust, mathematically verifiable.
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