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awesome-deeplearning-resources

Deep Learning and deep reinforcement learning research papers and some codes

caffe

Caffe: a fast open framework for deep learning.

convnet-benchmarks

Easy benchmarking of all publicly accessible implementations of convnets

cvpr2015

darknet

Convolutional Neural Networks

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

detect-track

fast-rcnn

Fast R-CNN

fb.resnet.torch

Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

goturn

Source code for paper: Learning to Track at 100 FPS with Deep Regression Networks, Held, et al. ECCV 2016

inception-v3.torch

Rethinking the Inception Architecture for Computer Vision

inception.torch

Torch port of https://github.com/google/inception

mc-cnn

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

mdnet

Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

mistune

The fastest markdown parser in pure Python with renderer feature.

myfirstwithgithub

Just try something new

opentld

C++ implementation of TLD

py-r-fcn

R-FCN with joint training and python support

rcnn

R-CNN: Regions with Convolutional Neural Network Features

rcnn-depth

Learning Rich Features from RGB-D Images for Object Detection and Segmentation

recipes

Lasagne recipes: examples, IPython notebooks, ...

resmatch

Implementation of "Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning"

resnext

Implementation of a classification framework from the paper Aggregated Residual Transformations for Deep Neural Networks

rrc_detection

Accurate Single Stage Detector Using Recurrent Rolling Convolution

theano

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

torch-rnn

Efficient, reusable RNNs and LSTMs for torch

torch7

http://torch.ch

vlfeat

An open library of computer vision algorithms