4 citations · 5 across the 8 of their papers we have counts for
9 papers · 1 filter
CPG-PAD: Concept-Informed Prompts Guided Presentation Attack Detection
Haoyuan Zhang, Xiangyu Zhu, Li Gao +3
Presentation Attack Detection (PAD) serves as a crucial safeguard for face recognition systems against presentation attacks such as printed photos, replayed videos, and 3D masks. D…
Reduce the Artifacts Bias for More Generalizable AI-Generated Image Detection
Yiheng Li, Yang Yang, Wenhao Wang +4
As the misuse of AI-generated images grows, generalizable image detection techniques are urgently needed. Recent state-of-the-art (SOTA) methods adopt aligned training datasets to…
DevFD: Developmental Face Forgery Detection by Learning Shared and Orthogonal LoRA Subspaces
Tianshuo Zhang, Li Gao, Siran Peng +2
The rise of realistic digital face generation and manipulation poses significant social risks. The primary challenge lies in the rapid and diverse evolution of generation technique…
Unifying Locality of KANs and Feature Drift Compensation Projection for Data-free Replay based Continual Face Forgery Detection
Tianshuo Zhang, Siran Peng, Li Gao +3
The rapid advancements in face forgery techniques necessitate that detectors continuously adapt to new forgery methods, thus situating face forgery detection within a continual lea…
DiffusionFF: A Diffusion-based Framework for Joint Face Forgery Detection and Fine-Grained Artifact Localization
Siran Peng, Haoyuan Zhang, Li Gao +5
The rapid evolution of deepfake technologies demands robust and reliable face forgery detection algorithms. While determining whether an image has been manipulated remains essentia…
MLLM-Enhanced Face Forgery Detection: A Vision-Language Fusion Solution
Siran Peng, Zipei Wang, Li Gao +5
Reliable face forgery detection algorithms are crucial for countering the growing threat of deepfake-driven disinformation. Previous research has demonstrated the potential of Mult…