3 papers
cs.CV2026
Towards Generalizable Deepfake Detection via Real Distribution Bias Correction
Ming-Hui Liu, Harry Cheng, Xin Luo +2
To generalize deepfake detectors to future unseen forgeries, most existing methods attempt to simulate the dynamically evolving forgery types using available source domain data. Ho…
cs.CV2026
Progressively Exploring and Exploiting Inference Data to Break Fine-Grained Classification Barrier
Li-Jun Zhao, Si-Yuan Zhang, Zhen-Duo Chen +2
Current fine-grained classification research primarily focuses on fine-grained feature learning. However, in real-world scenarios, fine-grained data annotation is challenging, and…
cs.CV2025
Federated Class-Incremental Learning with Prompting
Xin Luo, Fang-Yi Liang, Jiale Liu +3
As Web technology continues to develop, it has become increasingly common to use data stored on different clients. At the same time, federated learning has received widespread atte…