3 citations · 9 across the 5 of their papers we have counts for
5 papers
Improving Fairness in Deepfake Detection
Yan Ju, Shu Hu, Shan Jia +2
Despite the development of effective deepfake detectors in recent years, recent studies have demonstrated that biases in the data used to train these detectors can lead to disparit…
AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics
Shan Jia, Mingzhen Huang, Zhou Zhou +3
Recent advancements in language-image models have led to the development of highly realistic images that can be generated from textual descriptions. However, the increased visual q…
GLFF: Global and Local Feature Fusion for AI-synthesized Image Detection
Yan Ju, Shan Jia, Jialing Cai +2
With the rapid development of deep generative models (such as Generative Adversarial Networks and Diffusion models), AI-synthesized images are now of such high quality that humans…
Fusing Global and Local Features for Generalized AI-Synthesized Image Detection
Yan Ju, Shan Jia, Lipeng Ke +3
With the development of the Generative Adversarial Networks (GANs) and DeepFakes, AI-synthesized images are now of such high quality that humans can hardly distinguish them from re…
Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification
Yan Ju, Lingling Li, Licheng Jiao +3
Due to the limited amount and imbalanced classes of labeled training data, the conventional supervised learning can not ensure the discrimination of the learned feature for hypersp…