NS-Net: Decoupling CLIP Semantic Information through NULL-Space for Generalizable AI-Generated Image Detection
Fuente:
arXiv
Saved in:
| Main Authors: | Yan, Jiazhen, Wang, Fan, Jiang, Weiwei, Li, Ziqiang, Fu, Zhangjie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection
by: Yan, Jiazhen, et al.
Published: (2025)
by: Yan, Jiazhen, et al.
Published: (2025)
Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detection
by: Yan, Jiazhen, et al.
Published: (2025)
by: Yan, Jiazhen, et al.
Published: (2025)
How Noise Benefits AI-generated Image Detection
by: Li, Ziqiang, et al.
Published: (2025)
by: Li, Ziqiang, et al.
Published: (2025)
Is Artificial Intelligence Generated Image Detection a Solved Problem?
by: Li, Ziqiang, et al.
Published: (2025)
by: Li, Ziqiang, et al.
Published: (2025)
Beyond Text Prompts: Precise Concept Erasure through Text-Image Collaboration
by: Li, Jun, et al.
Published: (2026)
by: Li, Jun, et al.
Published: (2026)
Generalizable Deepfake Detection Based on Forgery-aware Layer Masking and Multi-artifact Subspace Decomposition
by: Zhang, Xiang, et al.
Published: (2026)
by: Zhang, Xiang, et al.
Published: (2026)
Decoupling Forgery Semantics for Generalizable Deepfake Detection
by: Ye, Wei, et al.
Published: (2024)
by: Ye, Wei, et al.
Published: (2024)
OmniAID: Decoupling Semantic and Artifacts for Universal AI-Generated Image Detection in the Wild
by: Guo, Yuncheng, et al.
Published: (2025)
by: Guo, Yuncheng, et al.
Published: (2025)
Low-rank Orthogonal Subspace Intervention for Generalizable Face Forgery Detection
by: Wang, Chi, et al.
Published: (2026)
by: Wang, Chi, et al.
Published: (2026)
When Detectors Forget Forensics: Blocking Semantic Shortcuts for Generalizable AI-Generated Image Detection
by: Shuai, Chao, et al.
Published: (2026)
by: Shuai, Chao, et al.
Published: (2026)
Decoupling Semantics and Fingerprints: A Universal Representation for AI-Generated Image Detection
by: Wang, Zhiyuan, et al.
Published: (2026)
by: Wang, Zhiyuan, et al.
Published: (2026)
DeeCLIP: A Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images
by: Keita, Mamadou, et al.
Published: (2025)
by: Keita, Mamadou, et al.
Published: (2025)
Scaling Exposes the Trigger: Input-Level Backdoor Detection in Text-to-Image Diffusion Models via Cross-Attention Scaling
by: Li, Zida, et al.
Published: (2026)
by: Li, Zida, et al.
Published: (2026)
Exploring the Collaborative Advantage of Low-level Information on Generalizable AI-Generated Image Detection
by: Zhou, Ziyin, et al.
Published: (2025)
by: Zhou, Ziyin, et al.
Published: (2025)
CausalCLIP: Causally-Informed Feature Disentanglement and Filtering for Generalizable Detection of Generated Images
by: Liu, Bo, et al.
Published: (2025)
by: Liu, Bo, et al.
Published: (2025)
Multimodal Conditional Information Bottleneck for Generalizable AI-Generated Image Detection
by: Qin, Haotian, et al.
Published: (2025)
by: Qin, Haotian, et al.
Published: (2025)
Physics-Aligned Spectral Mamba: Decoupling Semantics and Dynamics for Few-Shot Hyperspectral Target Detection
by: Gong, Luqi, et al.
Published: (2026)
by: Gong, Luqi, et al.
Published: (2026)
Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection
by: Yan, Zhiyuan, et al.
Published: (2024)
by: Yan, Zhiyuan, et al.
Published: (2024)
A Comprehensive Survey on Visual Concept Mining in Text-to-image Diffusion Models
by: Li, Ziqiang, et al.
Published: (2025)
by: Li, Ziqiang, et al.
Published: (2025)
Detecting AI-Generated Images via CLIP
by: Moskowitz, A. G., et al.
Published: (2024)
by: Moskowitz, A. G., et al.
Published: (2024)
Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection
by: Yermakov, Andrii, et al.
Published: (2025)
by: Yermakov, Andrii, et al.
Published: (2025)
Control-CLIP: Decoupling Category and Style Guidance in CLIP for Specific-Domain Generation
by: Jia, Zexi, et al.
Published: (2025)
by: Jia, Zexi, et al.
Published: (2025)
PGC: Peak-Guided Calibration for Generalizable AI-Generated Image Detection
by: Zhou, Xiaoyu, et al.
Published: (2026)
by: Zhou, Xiaoyu, et al.
Published: (2026)
Reduce the Artifacts Bias for More Generalizable AI-Generated Image Detection
by: Li, Yiheng, et al.
Published: (2026)
by: Li, Yiheng, et al.
Published: (2026)
GAMMA: Generalizable Alignment via Multi-task and Manipulation-Augmented Training for AI-Generated Image Detection
by: Yan, Haozhen, et al.
Published: (2025)
by: Yan, Haozhen, et al.
Published: (2025)
Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation
by: Wang, Yunnan, et al.
Published: (2024)
by: Wang, Yunnan, et al.
Published: (2024)
Transfer CLIP for Generalizable Image Denoising
by: Cheng, Jun, et al.
Published: (2024)
by: Cheng, Jun, et al.
Published: (2024)
Raising the Bar of AI-generated Image Detection with CLIP
by: Cozzolino, Davide, et al.
Published: (2023)
by: Cozzolino, Davide, et al.
Published: (2023)
CLIP-AGIQA: Boosting the Performance of AI-Generated Image Quality Assessment with CLIP
by: Tang, Zhenchen, et al.
Published: (2024)
by: Tang, Zhenchen, et al.
Published: (2024)
When Semantics Regulate: Rethinking Patch Shuffle and Internal Bias for Generated Image Detection with CLIP
by: Chu, Beilin, et al.
Published: (2025)
by: Chu, Beilin, et al.
Published: (2025)
Semantic Visual Anomaly Detection and Reasoning in AI-Generated Images
by: Tan, Chuangchuang, et al.
Published: (2025)
by: Tan, Chuangchuang, et al.
Published: (2025)
Towards Generalizable AI-Generated Image Detection via Image-Adaptive Prompt Learning
by: Li, Yiheng, et al.
Published: (2025)
by: Li, Yiheng, et al.
Published: (2025)
CLIP-Flow: A Universal Discriminator for AI-Generated Images Inspired by Anomaly Detection
by: Yuan, Zhipeng, et al.
Published: (2025)
by: Yuan, Zhipeng, et al.
Published: (2025)
DetailCLIP: Injecting Image Details into CLIP's Feature Space
by: Zhang, Zilun, et al.
Published: (2022)
by: Zhang, Zilun, et al.
Published: (2022)
Generalizable Detection of AI Generated Images with Large Models and Fuzzy Decision Tree
by: Wu, Fei, et al.
Published: (2026)
by: Wu, Fei, et al.
Published: (2026)
Generalizable AI-Generated Image Detection Based on Fractal Self-Similarity in the Spectrum
by: Xiao, Shengpeng, et al.
Published: (2025)
by: Xiao, Shengpeng, et al.
Published: (2025)
MediCLIP: Adapting CLIP for Few-shot Medical Image Anomaly Detection
by: Zhang, Ximiao, et al.
Published: (2024)
by: Zhang, Ximiao, et al.
Published: (2024)
MIRROR: Manifold Ideal Reference ReconstructOR for Generalizable AI-Generated Image Detection
by: Liu, Ruiqi, et al.
Published: (2026)
by: Liu, Ruiqi, et al.
Published: (2026)
DeCLIP: Decoupled Prompting for CLIP-based Multi-Label Class-Incremental Learning
by: Du, Kaile, et al.
Published: (2025)
by: Du, Kaile, et al.
Published: (2025)
Exploring the Adversarial Robustness of CLIP for AI-generated Image Detection
by: De Rosa, Vincenzo, et al.
Published: (2024)
by: De Rosa, Vincenzo, et al.
Published: (2024)
Similar Items
-
DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection
by: Yan, Jiazhen, et al.
Published: (2025) -
Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detection
by: Yan, Jiazhen, et al.
Published: (2025) -
How Noise Benefits AI-generated Image Detection
by: Li, Ziqiang, et al.
Published: (2025) -
Is Artificial Intelligence Generated Image Detection a Solved Problem?
by: Li, Ziqiang, et al.
Published: (2025) -
Beyond Text Prompts: Precise Concept Erasure through Text-Image Collaboration
by: Li, Jun, et al.
Published: (2026)