Shaip·Mar 4, 2025Anti-Spoofing in Face Recognition: Techniques for Liveness DetectionFacial recognition has become a key pillar of present security systems in smartphone authentication, banking, and surveillance. However…
Pranjal Ostwal·Mar 8, 2024Data preparation for Face Anti-Spoofing and Fraud DetectionFace recognition systems have become ubiquitous, providing convenient authentication in many applications. However, as these technologies…
Ayuvirgiana·Jan 25, 2024Web-based Face Recognition Attendance System with Anti SpoofingWe have made a web-based Facial Recognition Attendance System built with Python language and Streamlit framework. We made this project for…A response icon1A response icon1
InComputer Vision NotebyMoris·Dec 26, 2023PatchNet-Rethinking Pseudo-LiDAR Representation提出了一個稱為 PatchNet 的簡單而有效的面部反欺詐框架。其關鍵創新是將面部反欺詐任務重新定義為面部圖像局部區域的細粒度識別問題，也就是識別面部圖像不同局部區域的拍攝設備和材質組合。這種方法充分利用了局部區域中的微小差異特徵，可以大幅提高模型對 spoofing…
Fractal AI Research·Jun 6, 2023Face Anti-spoofing (FAS) 101 using RGB ImagesAs biometric technology continues to grow in popularity, facial recognition systems have become not only a crucial part of many industries…
InComputer Vision NotebyMoris·Apr 7, 2023FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofing該論文於2019年發表於CVPR, 有52個Reference
Abhay Garg·Feb 4, 2023PatchNET: A Simple Face Anti-Spoofing Framework.Face Spoofing refers to the attempts to fool a face recognition system by presenting image cut-outs, videos, card-masks instead of live…
InComputer Vision NotebyMoris·Jan 13, 2023Multi-Modal Face Anti-Spoofing Based on Central Difference Networks該論文於2020年發表於CVPR, 有42個Reference
InComputer Vision NotebyMoris·Jan 11, 2023Searching Central Difference Convolutional Networks forFace Anti-spoofing該論文於2020年發表於CVPR, 有200個Reference
InComputer Vision NotebyMoris·Dec 20, 2022PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofing該論文於2020年發表於IEEE, 有14個Reference, 在Chalearn Multi-modal Cross-ethnicity Face anti-spoofing Recognition Challenge@CVPR2020最終排名中獲得第三名
