4 citations · 8 across the 9 of their papers we have counts for
9 papers
CD^2: Constrained Dataset Distillation for Few-Shot Class-Incremental Learning
Kexin Bao, Daichi Zhang, Hansong Zhang +3
Few-shot class-incremental learning (FSCIL) receives significant attention from the public to perform classification continuously with a few training samples, which suffers from th…
Enhancing Frequency Forgery Clues for Diffusion-Generated Image Detection
Daichi Zhang, Tong Zhang, Shiming Ge +1
Diffusion models have achieved remarkable success in image synthesis, but the generated high-quality images raise concerns about potential malicious use. Existing detectors often s…
Leveraging Hierarchical Image-Text Misalignment for Universal Fake Image Detection
Daichi Zhang, Tong Zhang, Jianmin Bao +2
With the rapid development of generative models, detecting generated fake images to prevent their malicious use has become a critical issue recently. Existing methods frame this ch…
Interpret the Predictions of Deep Networks via Re-Label Distillation
Yingying Hua, Shiming Ge, Daichi Zhang
Interpreting the predictions of a black-box deep network can facilitate the reliability of its deployment. In this work, we propose a re-label distillation approach to learn a dire…
Look Through Masks: Towards Masked Face Recognition with De-Occlusion Distillation
Chenyu Li, Shiming Ge, Daichi Zhang +1
Many real-world applications today like video surveillance and urban governance need to address the recognition of masked faces, where content replacement by diverse masks often br…
Learning Natural Consistency Representation for Face Forgery Video Detection
Daichi Zhang, Zihao Xiao, Shikun Li +3
Face Forgery videos have elicited critical social public concerns and various detectors have been proposed. However, fully-supervised detectors may lead to easily overfitting to sp…
Latent Spatiotemporal Adaptation for Generalized Face Forgery Video Detection
Daichi Zhang, Zihao Xiao, Jianmin Li +1
Face forgery videos have caused severe public concerns, and many detectors have been proposed. However, most of these detectors suffer from limited generalization when detecting vi…
Deepfake Video Detection with Spatiotemporal Dropout Transformer
Daichi Zhang, Fanzhao Lin, Yingying Hua +3
While the abuse of deepfake technology has caused serious concerns recently, how to detect deepfake videos is still a challenge due to the high photo-realistic synthesis of each fr…
Interpretable Face Manipulation Detection via Feature Whitening
Yingying Hua, Daichi Zhang, Pengju Wang +1
Why should we trust the detections of deep neural networks for manipulated faces? Understanding the reasons is important for users in improving the fairness, reliability, privacy a…