HZQ-GitHub's repositories
MTCNN_face_detection_alignment
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
awesome-object-proposals
A curated list of object proposals resources for object detection
caffe
Caffe: a fast open framework for deep learning.
Caffe_Manual
Caffe使用教程
CAR-DETECTION
car detection using the UIUC car database
CenterLoss_Caffe_Mnist
It's the script of Center loss on mnist dataset running on Caffe.
DeepVisualization
Visualizing Deep Neural Network by Alternately Image Blurring and Deblurring
faster_rcnn
Faster R-CNN
head-pose-estimation-and-face-landmark
head pose estimation
hello-world
This is a repository named hello-world.
LargeMargin_Softmax_Loss
Implementation for <Large-Margin Softmax Loss for Convolutional Neural Networks> in ICML'16
mobile-id
MobileID: Face Model Compression by Distilling Knowledge from Neurons
MTCNN-1
Repository for "Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks", implemented with Caffe, C++ interface.
mtcnn-2
基于caffe的mtcnn训练实现，非常容易非常简单，并且有配套的纯c++版本的mtcnn-light
mtcnn-caffe
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
MTCNN-light
this repository is the implementation of MTCNN with no framework, Just need opencv and openblas, support linux and windows
mxnet
efficient, flexible, distributed deep learning framework
NormFace
NormFace: L2 HyperSphere Embedding for Face Verification, 99.21% on LFW
py-faster-rcnn
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version
sdm
Supervised Descent Method Apply to Face Alignment, and Head Pose Estimation with Linear Regression. It is cross-platfrom, easily compile in windows, ubuntu, even in Android & iOS.
tiny
Tiny Face Detector, CVPR 2017
vehicle_detection_haarcascades
Vehicle Detection by Haar Cascades with OpenCV
Vehicle_Detection_Recognition
This is a Matlab lesson design for vehicle detection and recognition. Using cifar-10Net to training a RCNN, and finetune AlexNet to classify. Thanks to Cars Dataset:http://ai.stanford.edu/~jkrause/cars/car_dataset.html