arXiv (All)
open access
FeatMark: Feature-level Watermark Protection against Mimicry Attacks with Diffusion Models
Text-to-image diffusion models enable data-efficient "mimicry" attacks, wherein adversaries fine-tune the model on a handful of public photos to synthesize convincing forgeries of a target individual. A common countermeasure is to embed imperceptible, low-energy watermarks, yet recent studies show t
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Rethinking Forgery Attacks on Semantic Watermarks in Black-Box Settings: A Geometric Distortion Perspective#321755
- Removing the Watermark Is Not Enough: Forensic Stealth in Generative-AI Watermark Removal#684447
- Removing the Watermark Is Not Enough: Forensic Stealth in Generative-AI Watermark Removal#682672
- DRIFT: Removing Diffusion Watermarks by Deflecting the Generative Trajectory#985586
- Official Review · NEURIPS 2024#787081
Record · ID 1105539
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive