qidiso Goto Github PK
Name: qidiso
Type: User
Bio: deep learning .face recognition, pose/action recognition
Name: qidiso
Type: User
Bio: deep learning .face recognition, pose/action recognition
This is tensorflow implementation for paper "Deep Image Matting"
Pytorch implementation of deep person re-identification models.
Improving Fast And Accurate 3D Hand Pose Estimation
Deep learning based one class classification code targeting one class image classification. Tests carried out on Abnormal image detection, Novel image detection and Active Authentication reported state of the art results.
Dataset, necessary Scripts and trained SSD Model for detecting Hands in Realtime.
A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body
The implementation of an algorithm presented in the CVPR18 paper: "Detect-and-Track: Efficient Pose Estimation in Videos"
Code for "Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detection"
Facial detection, landmark tracking and expression transfer library for Windows, Linux and Mac
JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
Face-authentication system enterely written on C++ with OpenCV and Qt third party library. Face-antispoofing procedure is included.
Face Liveness Detection in C++, MATLAB and Python.
ancient code with deprecated function, refactoring required
Deep Texture feature extraction and implementing Local Binary Pattern(LBP)-based Convolutional Neural Network
I optimized OpenTLD making it run faster and better for face tracking.
Codes for face age estimation with transfer learning of inception v3 model and tensorflow
Training on multiple datasets with ''mixed batches'' strategy
This repository is the implementation of face detection in real time using YOLOv3 framework with keras(tensorflow backend). For use in embeded devices, so I choose a computation-efficient CNN architecture named ShuffleNet version 2 and train it from scratch(about 50 epoches) on FDDB.
These are a set of tools using OpenCV, Tensorflow and Keras, with which you can generate your own model of facial landmark detection and demonstrate the effect of newly-generated model easily.
Millions People Face Desc, to describe a face in gender, age, and emotion. #gender/age classification#, #gender/age detection#, #gender/age prediction#
Align a face in profile to front view
Vision-Based Fallen Person Detection for the Elderly
pytorch realtime multi person keypoint estimation
Code for 3rd Place Solution in Face Anti-spoofing Attack Detection Challenge @ CVPR2019,model only 0.35M!!! 1.88ms(CPU)
real-time fire detection in video imagery using a convolutonal neural network - from our ICIP 2018 paper (Dunnings / Breckon)
Hand Gestures for Drone Control Using Deep Learning :fist: :hand: :helicopter: :point_up: :raised_hands:
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.