A training-free watermarking framework that embeds watermarks into diffusion super-resolution noise and extracts them via DDIM inversion, reaching 99.46% bit accuracy under standard distortions and 89.29% under adaptive attacks on MS-COCO.
The string s is then replicated fc · f 2 hw times and reshaped into its diffused version sd with the shape (c, h, w)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolution
A training-free watermarking framework that embeds watermarks into diffusion super-resolution noise and extracts them via DDIM inversion, reaching 99.46% bit accuracy under standard distortions and 89.29% under adaptive attacks on MS-COCO.