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awesome-object-proposals

A curated list of object proposals resources for object detection

caffe

Caffe: a fast open framework for deep learning.

caffe-face-centerloss

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

enet-training

faster_rcnn

Faster R-CNN

head-pose-estimation-and-face-landmark

head pose estimation

hello-world

This is a repository named hello-world.

hzq-github.github.io

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

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

mtcnn_face_detection_alignment

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

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