20 citations · 179 across the 97 of their papers we have counts for
23 papers · 1 filter
A Self-Learning Multimodal Approach for Fake News Detection
Hao Chen, Hui Guo, Baochen Hu +5
The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While mach…
HMGIE: Hierarchical and Multi-Grained Inconsistency Evaluation for Vision-Language Data Cleansing
Zihao Zhu, Hongbao Zhang, Guanzong Wu +2
Visual-textual inconsistency (VTI) evaluation plays a crucial role in cleansing vision-language data. Its main challenges stem from the high variety of image captioning datasets, w…
Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection
Delong Zhu, Yuezun Li, Baoyuan Wu +3
Face-swapping DeepFakes have become an escalating societal concern, attracting increasing attention in recent years. To counter this, we investigate a new proactive defense framewo…
Forensics Adapter: Unleashing CLIP for Generalizable Face Forgery Detection
Xinjie Cui, Yuezun Li, Delong Zhu +3
We describe Forensics Adapter, an adapter network designed to transform CLIP into an effective and generalizable face forgery detector. Although CLIP is highly versatile, adapting…
Meta-Learning with Heterogeneous Tasks
Zhaofeng Si, Shu Hu, Kaiyi Ji +1
Meta-learning is a general approach to equip machine learning models with the ability to handle few-shot scenarios when dealing with many tasks. Most existing meta-learning methods…
X2-DFD: A framework for eXplainable and eXtendable Deepfake Detection
Yize Chen, Zhiyuan Yan, Guangliang Cheng +3
This paper proposes X2-DFD, an eXplainable and eXtendable framework based on multimodal large-language models (MLLMs) for deepfake detection, consisting of three key stages. The fi…