98 citations · 197 across the 12 of their papers we have counts for
12 papers
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…
Image Copy-Move Forgery Detection via Deep Cross-Scale PatchMatch
Yingjie He, Yuanman Li, Changsheng Chen +1
The recently developed deep algorithms achieve promising progress in the field of image copy-move forgery detection (CMFD). However, they have limited generalizability in some prac…
Forensicability Assessment of Questioned Images in Recapturing Detection
Changsheng Chen, Lin Zhao, Rizhao Cai +3
Recapture detection of face and document images is an important forensic task. With deep learning, the performances of face anti-spoofing (FAS) and recaptured document detection ha…
Fusing Multiscale Texture and Residual Descriptors for Multilevel 2D Barcode Rebroadcasting Detection
Anselmo Ferreira, Changcheng Chen, Mauro Barni
Nowadays, 2D barcodes have been widely used for advertisement, mobile payment, and product authentication. However, in applications related to product authentication, an authentic…
Deep Learning-based Forgery Attack on Document Images
Lin Zhao, Changsheng Chen, Jiwu Huang
With the ongoing popularization of online services, the digital document images have been used in various applications. Meanwhile, there have emerged some deep learning-based text…
Domain Generalization for Document Authentication against Practical Recapturing Attacks
Changsheng Chen, Shuzheng Zhang, Fengbo Lan +1
Recapturing attack can be employed as a simple but effective anti-forensic tool for digital document images. Inspired by the document inspection process that compares a questioned…
DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing
Rizhao Cai, Haoliang Li, Shiqi Wang +2
Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i.e., to glance at the example globally first and then carefull…
Detection of Information Hiding at Anti-Copying 2D Barcodes
Ning Xie, Ji Hu, Junjie Chen +2
This paper concerns the problem of detecting the use of information hiding at anti-copying 2D barcodes. Prior hidden information detection schemes are either heuristicbased or Mach…
Low-Cost Anti-Copying 2D Barcode by Exploiting Channel Noise Characteristics
Ning Xie, Qiqi Zhang, Ji Hu +2
In this paper, for overcoming the drawbacks of the prior approaches, such as low generality, high cost, and high overhead, we propose a Low-Cost Anti-Copying (LCAC) 2D barcode by e…
Layer Pruning for Accelerating Very Deep Neural Networks
Weiwei Zhang, Changsheng chen, Xuechun Wu +4
In this paper, we propose an adaptive pruning method. This method can cut off the channel and layer adaptively. The proportion of the layer and the channel to be cut is learned ada…
Learning deep forest with multi-scale Local Binary Pattern features for face anti-spoofing
Rizhao Cai, Changsheng Chen
Face Anti-Spoofing (FAS) is significant for the security of face recognition systems. Convolutional Neural Networks (CNNs) have been introduced to the field of the FAS and have ach…
A Systematic Scheme for Measuring the Performance of the Display-Camera Channel
Changsheng Chen, Wai Ho Mow
Display-camera communication has become a promising direction in both computer vision and wireless communication communities. However, the consistency of the channel measurement is…