3 papers
cs.CV2025
Dual Data Alignment Makes AI-Generated Image Detector Easier Generalizable
Ruoxin Chen, Junwei Xi, Zhiyuan Yan +8
Existing detectors are often trained on biased datasets, leading to the possibility of overfitting on non-causal image attributes that are spuriously correlated with real/synthetic…
cs.CV2025
All Patches Matter, More Patches Better: Enhance AI-Generated Image Detection via Panoptic Patch Learning
Zheng Yang, Ruoxin Chen, Zhiyuan Yan +8
The exponential growth of AI-generated images (AIGIs) underscores the urgent need for robust and generalizable detection methods. In this paper, we establish two key principles for…
cs.CV2024
Decoupled Data Augmentation for Improving Image Classification
Ruoxin Chen, Zhe Wang, Ke-Yue Zhang +5
Recent advancements in image mixing and generative data augmentation have shown promise in enhancing image classification. However, these techniques face the challenge of balancing…