Residual Transferability in Neural Image Watermarking

arXiv:2609.32241 · cs.CR, cs.CV · Submitted 2026-09-26 · Read on arXiv

cs.CR, cs.CV

Submitted: 2026-09-26

Updated: 2026-09-26

Project page: https://facebookresearch.github.io/content-seal

Terminology

• Transferability — 31× in this paper · explained in 4 episodes
• Robustness — 21× in this paper · explained in 5 episodes
• Verification — 12× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Diffusion Model — 6× in this paper · explained in 8 episodes
• Diffusion Models — 6× in this paper · explained in 6 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Provenance — 4× in this paper · explained in 4 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• AUC — 2× in this paper · explained in 2 episodes
• Attack Success Rate — 2× in this paper
• CVF International Conference on Computer Vision — 2× in this paper
• Calibration — 2× in this paper · explained in 7 episodes
• Core — 2× in this paper · explained in 2 episodes
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptive Mechanism — 1× in this paper · explained in 1 episode
• Adaptivity — 1× in this paper · explained in 1 episode
• Adversarial Training — 1× in this paper · explained in 1 episode
• Agentic Reasoning — 1× in this paper · explained in 1 episode
• Attack Success Rate (ASR) — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Bit Error Rate — 1× in this paper
• Decode — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• True Positive Rate — 1× in this paper

Sources

• WMCopier: Forging Invisible Image Watermarks on Arbitrary Images
• Deep Residual Learning for Image Recognition
• CSGuard: Toward Forgery-Resistant Watermarking in Diffusion Models via Compressed Sensing Constraint
• Sponge Tool Attack: Stealthy Denial-of-Efficiency against Tool-Augmented Agentic Reasoning
• BadWAM: When World-Action Models Dream Right but Act Wrong
• Harnessing Frequency Spectrum Insights for Image Copyright Protection Against Diffusion Models
• A ConvNet for the 2020s
• Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models
• Compositional Adversarial Training for Robust Visual Watermarking
• Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
• Pixel Seal: Adversarial-only training for invisible image and video watermarking
• Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection
• Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust
• Robust Invisible Video Watermarking with Attention

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