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100-days-of-ml-code

100 Days of ML Coding

ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

awesome-algorithm-interview

算法工程师(人工智能CV方向)面试问题及相关资料

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

continuouscrf-cnn

Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation in CVPR 2017

cs229

cv

Affine Transformation to rectify image after rotated

data-analysis

Data Science Using Python

datacleaner

The premier open source Data Quality solution

datart

Datart is a next generation Data Visualization Open Platform

dorn

facial-expression-recognition.pytorch

A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset

fake-smile-detection-model

Fake Smile Detection Model using CNNs in Python

fe_intensity

master project: recognising facial expression intensity

flownet2-pytorch

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

ganet

GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

genki

GENKI数据集是由加利福尼亚大学的机器概念实验室收集。该数据集包含GENKI-R2009a,GENKI-4K,GENKI-SZSL三个部分。GENKI-R2009a包含11159个图像，GENKI-4K包含4000个图像，分为“笑”和“不笑”两种，每个图片的人脸的尺度大小，姿势，光照变化，头的转动等都不一样，专门用于做笑脸识别。GENKI-SZSL包含3500个图像，这些图像包括广泛的背景，光照条件，地理位置，个人身份和种族等。

high-res-stereo

Hierarchical Deep Stereo Matching on High Resolution Images, CVPR 2019.

lstm

Minimal, clean example of lstm neural network training in python, for learning purposes.

machinelearning

Linear Regression, Ridge Regression, SVM, Facial Expression Recognition

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

mc-cnn

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

monodepth-cpp

Tensorflow C++ implementation for single-image depth estimation (Monodepth)

motbeyondpixels

Monocular multi-object tracking using simple and complementary 3D and 2D cues (ICRA 2018)

mtcnn

基于caffe的mtcnn训练实现，可以训练一个自己的有效的目标检测算法，非常容易非常简单，并且有配套的纯c++版本的mtcnn-light

mx-maskrcnn

An MXNet implementation of Mask R-CNN

pandas-python-data-analysis-playground

🐍 Data Analysis with the Pandas Library & Notes 📊📈

pytorchconverter

Pytorch model to caffe & ncnn

rpg_open_remode

This repository contains an implementation of REMODE (REgularized MOnocular Depth Estimation), as described in the paper.