There are 8 repositories under biometrics topic.
ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!
Horilla is a free and open source HR software.
Use Apple FaceID or TouchID authentication in your app using BiometricAuthentication.
Messenger Clone - Real-time iOS Chat with Firebase Firestore written in Swift
A Simple Expense Tracker App built to demonstrate the use of SwiftUI, CoreData, Charts, Biometrics (Face & Touch ID), Export CSV and MVVM Architecture.
A simple use webview integrated w/ native features & plugin support for building hybrid apps.
Code and information for face image quality assessment with SER-FIQ
Face Recognition FRVT, Face Liveness Detection, Face Recognition , Face Liveness, Face Identification, Face Compare, Face Matching, Face Pose, Face Expression, Face Attributes, Face Landmarks, Face Representation, Face Reconstruction
CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!
Face Recognition on NIST FRVT Top Ranked, Face Liveness Detection Engine on iBeta 2 Certified, 3D Face Anti Spoofing, Face Detection, Face Matching, Face Analysis, Face Sentiment, Face Alignment, Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution on Android
Quick unlock KeePass 2 database using biometrics with Windows Hello
Cordova Plugin for fingerprint sensors (and FaceID) with Android and iOS support
Open-source device for measuring cardiograpgy signals with a GUI for easier handling and additional software for analyzing the data.
Fingerprint recognition engine for Java that takes a pair of human fingerprint images and returns their similarity score. Supports efficient 1:N search.
3D Passive Face Liveness Detection (Anti-Spoofing) & Deepfake detection. A single image is needed to compute liveness score. 99,67% accuracy on our dataset and perfect scores on multiple public datasets (NUAA, CASIA FASD, MSU...).
Using oriented gabor filters to enhance fingerprint images
Django Authentication Backend For Passkeys
simple interface to verify user authenticity
Face Recognition SDK Flutter(Android, iOS), Face Liveness Detection, Face Landmarks, Face Recognition, Face Liveness, Face Pose, Face Expression, Face attributes, Face Identification, Face Representation, Face Reconstruction
3D Passive Face Liveness Detection! Supports Face Detection, Face Matching, Face Analysis, Face Sentiment, Face Alignment, Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution on Android
EDCC: An efficient and accurate algorithm for palmprint recognition.
This is an Android project allowing you to use the advanced biometric authorization features.
Extract minutiae features from fingerprint images
Code and models for paper "Robust Minutiae Extractor: Integrating Deep Networks and Fingerprint Domain Knowledge" at International Conference on Biometrics (ICB) 2018
Curated collection of human fingerprint datasets suitable for research and evaluation of fingerprint recognition algorithms.
CVPR 2022: Cross-Modal Perceptionist: Can Face Geometry be Gleaned from Voices?
Official repository for CVPR2023 paper, CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability
Deep Learning-Based Gait Recognition Using Smartphones in the Wild
Braavos Account Contract for Starknet
EdgeFace: Efficient Face Recognition Model for Edge Devices [TBIOM 2024] the winner of compact track of IJCB 2023 Efficient Face Recognition Competition
Use fingerprint readers with a Linux desktop environment
Signature recognition is a behavioural biometric. It can be operated in two different ways: Static: In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”. Dynamic: In this mode, users write their signature in a digitizing tablet, which acquires the signature in real time. Another possibility is the acquisition by means of stylus-operated PDAs. Some systems also operate on smart-phones or tablets with a capacitive screen, where users can sign using a finger or an appropriate pen. Dynamic recognition is also known as “on-line”. Dynamic information usually consists of the following information: