2 citations · 5 across the 5 of their papers we have counts for
5 papers
VRAG-DFD: Verifiable Retrieval-Augmentation for MLLM-based Deepfake Detection
Hui Han, Shunli Wang, Yandan Zhao +2
In Deepfake Detection (DFD) tasks, researchers proposed two types of MLLM-based methods: complementary combination with small DFD detectors, or static forgery knowledge injection.…
Align, Don't Blend: Orthogonal Supervision Disentanglement As the Key to Generalizable AI-Generated Image Detection
Ruoxin Chen, Jiahui Gao, Kaiqing Lin +5
Recent advances in AI-Generated Image (AIGI) detection have largely focused on model architectures, loss design, and training strategies, while overlooking a more fundamental facto…
A Quality-Centric Framework for Generic Deepfake Detection
Wentang Song, Zhiyuan Yan, Yuzhen Lin +6
Detecting AI-generated images, particularly deepfakes, has become increasingly crucial, with the primary challenge being the generalization to previously unseen manipulation method…
Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning
Zhiyuan Yan, Yandan Zhao, Shen Chen +5
Three key challenges hinder the development of current deepfake video detection: (1) Temporal features can be complex and diverse: how can we identify general temporal artifacts to…
DF40: Toward Next-Generation Deepfake Detection
Zhiyuan Yan, Taiping Yao, Shen Chen +8
We propose a new comprehensive benchmark to revolutionize the current deepfake detection field to the next generation. Predominantly, existing works identify top-notch detection al…