ysc703's starred repositories
LFD-A-Light-and-Fast-Detector
LFD is a big update upon LFFD. Generally, LFD is a multi-class object detector characterized by lightweight, low inference latency and superior precision. It is for real-world appilcations.
Semi-Siamese-Training
"Semi-Siamese Training for Shallow Face Learning"
FaceImageQuality
Code and information for face image quality assessment with SER-FIQ
LFFD-A-Light-and-Fast-Face-Detector-for-Edge-Devices
A light and fast one class detection framework for edge devices. We provide face detector, head detector, pedestrian detector, vehicle detector......
arcface-caffe
insightface-caffe
facerecognize-for-mobile-phone
适用于移动端的人脸识别模型,计算量与mobilefacenet相同,但megaface上提升了2%+
faceboxes_plate
plate
light-LPR
Light-LPR is an open source project aimed at license plate recognition that can run on embedded devices, mobile phones, and x86 platforms. It aims to support license plate recognition in various scenarios. The accuracy rate of license plate character recognition exceeds 99.95%, and the comprehensive recognition accuracy rate exceeds 99.%, Support multi-country and multilingual license plate recognition.
alpr-unconstrained
License Plate Detection and Recognition in Unconstrained Scenarios
MXNet-EfficientNet
A Gluon Implement of EfficientNet
insightface
State-of-the-art 2D and 3D Face Analysis Project
face.evoLVe
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
sphereface-plus
SphereFace+ Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.
License-Plate-Detect-Recognition-via-Deep-Neural-Networks-accuracy-up-to-99.9
works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate
Joint-Face-Detection-and-Alignment
Caffe and Python implementation of Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
MXNet2Caffe
Convert MXNet model to Caffe model
caffe-mobilenet_v2
caffe based mobilenet v2 deploy
sphereface
Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.