167 citations · 235 across the 12 of their papers we have counts for
13 papers
Generalized Face Forgery Detection via Adaptive Learning for Pre-trained Vision Transformer
Anwei Luo, Rizhao Cai, Chenqi Kong +4
With the rapid progress of generative models, the current challenge in face forgery detection is how to effectively detect realistic manipulated faces from different unseen domains…
S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens
Rizhao Cai, Zitong Yu, Chenqi Kong +4
Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces. State-of-the-art FAS techniques predominantly rely on de…
Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detection
Anwei Luo, Chenqi Kong, Jiwu Huang +3
Face forgery detection is essential in combating malicious digital face attacks. Previous methods mainly rely on prior expert knowledge to capture specific forgery clues, such as n…
Enhancing General Face Forgery Detection via Vision Transformer with Low-Rank Adaptation
Chenqi Kong, Haoliang Li, Shiqi Wang
Nowadays, forgery faces pose pressing security concerns over fake news, fraud, impersonation, etc. Despite the demonstrated success in intra-domain face forgery detection, existing…
M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System
Chenqi Kong, Kexin Zheng, Yibing Liu +3
Face presentation attacks (FPA), also known as face spoofing, have brought increasing concerns to the public through various malicious applications, such as financial fraud and pri…
Two-branch Multi-scale Deep Neural Network for Generalized Document Recapture Attack Detection
Jiaxing Li, Chenqi Kong, Shiqi Wang +1
The image recapture attack is an effective image manipulation method to erase certain forensic traces, and when targeting on personal document images, it poses a great threat to th…