🚀 | UniFace: A Comprehensive Library for Face Detection, Recognition, Landmark Analysis, Age, and Gender Detection.
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Updated
Nov 7, 2025 - Python
🚀 | UniFace: A Comprehensive Library for Face Detection, Recognition, Landmark Analysis, Age, and Gender Detection.
iBeta (Level 2) Certified, Single-Image Based Face Liveness Detection (Face Anti Spoofing) Server SDK
Face Recognition on NIST FRVT Top Ranked, Face Detection, Face Matching, Face Analysis, Face Sentiment, Face Alignment, Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution on Windows
FaceXlib plus aims at providing ready-to-use face-related functions based on current SOTA or most popular open-source methods while be compatible with facexlib.
Face Recognition on NIST FRVT Top Ranked, Face Detection, Face Matching, Face Analysis, Face Sentiment, Face Alignment, Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution on Linux
iBeta (Level 2) Certified, Single-Image Based Face Liveness Detection (Face Anti Spoofing) Server SDK
iBeta (Level 2) Certified, Single-Image Based Face Liveness Detection (Face Anti Spoofing) Server SDK
MiniAiLive's Complete Document Liveness Detection Solution for Digital Onboarding
Face Recognition, Face Liveness Detection, Face Attributes, Mask Detection, Emotion Detection Online Demo
Age and Gender Estimation in Crowd Scenes
INA's library with pretrained models for gender and age prediction from faces.
The Fashion Trend Analyzer is designed to identify and record seasonal costume patterns among different age groups and genders.
Pytorch implementation of NDDR-CNN (Neural Discriminative Dimensionality Reduction CNN)
In this project , we have gender and age detection using open cv (python) . Wherever your face is detected it will tell your gender and age as per your face is detected .
This repo contains, training material, dlib implementation, tensorflow implementation and an own made complete system implementation with a parse-controller.
[ D&A Conference ] 사진에서 배경에 존재하는 다른 사람들의 얼굴을 임의로 변환시켜주는 프로젝트
基于人脸关键区域提取的人脸识别(LFW:99.82%+ CFP_FP:98.50%+ AgeDB30:98.25%+)
This project is mainly based on Convolution Neural Network and OpenCV.
Steven C. Y. Hung, Jia-Hong Lee, Timmy S. T. Wan, Chein-Hung Chen, Yi-Ming Chan and Chu-Song Chen. "Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning" 2019 ACM on International Conference on Multimedia Retrieval
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