Effective Synthetic Image Detection via Noise Residual Clustering

arXiv:2607.10695 · cs.CV, cs.CR · Submitted 2026-07-12 · Read on arXiv

Caihui Yan, Gang Cao, Huawei Tian, Zhen Li, Yuhang Zhai

cs.CV, cs.CR

Submitted: 2026-07-12

Code: https://github.com/multimediaFor/NoiseCluSID

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 25× in this paper · explained in 1 episode
• Clustering — 21× in this paper · explained in 2 episodes
• Generalization — 15× in this paper · explained in 13 episodes
• Transformer — 14× in this paper · explained in 2 episodes
• Diffusion Model — 11× in this paper · explained in 8 episodes
• Trace — 9× in this paper · explained in 2 episodes
• Feature Extraction — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Generative Model — 7× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Diffusion Models — 6× in this paper · explained in 6 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Generative Models — 5× in this paper · explained in 3 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Adaptive Weighting — 3× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 3× in this paper · explained in 2 episodes
• Reconstruction Error — 3× in this paper · explained in 2 episodes
• Average Precision — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Dynamic Weighting — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Adversarial Networks (GANs) — 1× in this paper · explained in 3 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Over-smoothing — 1× in this paper · explained in 4 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Training-Free Framework — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• Hierarchical Text-Conditional Image Generation with CLIP Latents
• RIGID: A Training-free and Model-Agnostic Framework for Robust AI-Generated Image Detection
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection
• Large Scale GAN Training for High Fidelity Natural Image Synthesis

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