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2016_super_resolution

super resolution 2015ICCV Image Super-Resolution Using Deep Convolutional Networks

2s-tl

A two-stage transfer learning code in MATLAB

activetransferlearning

Code for various active transfer learning projects.

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

alphago

A replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search," details of which can be found on their website.

atldgp

Asymmetric Transfer Learning with Deep Gaussian Processes

autoencoding_beyond_pixels

Generative image model with learned similarity measures

awesome-deep-vision

A curated list of deep learning resources for computer vision

awesome-python-cn

Python资源大全中文版，内容包括：Web框架、网络爬虫、网络内容提取、模板引擎、数据库、数据可视化、图片处理、文本处理、自然语言处理、机器学习、日志、代码分析等

basicsr

Basic Super-Resolution codes for development. Includes ESRGAN, SFT-GAN for training and testing.

buildingmachinelearningsystemswithpython

Source Code for the book Building Machine Learning Systems with Python

caffe

Caffe: a fast open framework for deep learning.

caffe-cvprw15

:heart::coffee: Deep Learning of Binary Hash Codes for Fast Image Retrieval (CVPRW15)

caffe-facialkp

Facial keypoints extraction using Caffe

caffe-lmdbcreation-multilabel

Creation of LMDB for training a multi-label loss in Caffe

caffe-utils

Utilities for preparing the data and automating procedures

ccnf

Libraries for training and testing Continuous Conditional Neural Fields with a number of sample problems and other baselines.

clm-framework

CLM-framework (a.k.a Cambridge Face Tracker) is a framework for various Constrained Local Model based face tracking and landmark detection algorithms and their extensions/applications. Includes CLM-Z and CLNF.

cnn-for-image-retrieval

:sunrise:The code of post "Image retrieval using MatconvNet and pre-trained imageNet"

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

coursera-machine-learning

source from exercises in Coursera.

courseraml

I'm taking Andrew Ng's Machine Learning course on Coursera and doing the homework assigments... but, on my own in python because Octave? Really?

cp11fall_project1

Implementation of Edge-Preserving Multiscale Image Decomposition Based on Local Extrema

cvpr18-sftgan

Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform

cvpr2016_stylenet

Code for our CVPR 2016 paper on Fashion styles in 128 floats.

dcgan-autoencoder

dcgan-completion.tensorflow

Image Completion with Deep Learning in TensorFlow

dcgan-tensorflow

A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

dcgan.torch

A torch implementation of http://arxiv.org/abs/1511.06434

dcscn-super-resolution

A tensorflow implementation of "Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network", a deep learning based Single-Image Super-Resolution (SISR) model.