Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/MichaelXin/Awesome-Caffe

Awesome Caffe
https://github.com/MichaelXin/Awesome-Caffe

List: Awesome-Caffe

Last synced: about 2 months ago
JSON representation

Awesome Caffe

Host: GitHub
URL: https://github.com/MichaelXin/Awesome-Caffe
Owner: MichaelXin
License: cc0-1.0
Created: 2016-09-21T01:46:31.000Z (about 8 years ago)
Default Branch: master
Last Pushed: 2019-09-05T06:12:18.000Z (over 5 years ago)
Last Synced: 2024-05-22T04:00:44.307Z (7 months ago)
Size: 50.8 KB
Stars: 220
Watchers: 25
Forks: 89
Open Issues: 0
Metadata Files:
- Readme: README.md
- Contributing: contributing.md
- License: LICENSE

Awesome Lists containing this project

awesomeai - Caffe
awesome-ai-awesomeness - Caffe
awesome-ai-awesomeness - Caffe
ultimate-awesome - Awesome-Caffe - Awesome Caffe. (Other Lists / PowerShell Lists)

README

        # Awesome Caffe  [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/jtoy/awesome)

This page contains a curated list of awesome Caffe examples, tutorials and blogs. It is inspired by awesome-php and awesome-machine-learning.

## Contributing

If you think I have missed out on something (or) have any suggestions (papers, implementations and other resources), feel free to pull a request

Feedback and contributions are welcome!

## Table of Contents

- [1. Tutorials](#Tutorials)

- [2. Vision](#Vision)

- [3. NLP](#NLP)

- [4. Speech](#Speech)

- [5. Building Blocks](#Building)

- [6. Tools](#Tools)

============================================================================================================

## Books

- [Deep Learning - Ian Goodfellow and Yoshua Bengio and Aaron Courville](http://www.deeplearningbook.org/)

- [Deep Learning (Simplified Chinese)](https://github.com/exacity/deeplearningbook-chinese)

## 1. Tutorials

- [DIY Deep Learning for Vision with Caffe](https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p)

- [Tutorial Documentation](http://caffe.berkeleyvision.org/tutorial/)

- [Tutorial Documentation (Simplified Chinese)](http://caffecn.cn/?/page/tutorial)

## 2. Vision

>> ### 2.1 Image Classification

>> - [ResNet-v3](https://github.com/terrychenism/ResNeXt)

>> - [denseNet](https://github.com/liuzhuang13/DenseNet)

>> - [Deep Residual Networks](https://github.com/KaimingHe/deep-residual-networks)

>> - [Highway Networks](https://github.com/flukeskywalker/highway-networks)

>> - [Deep-Compression-AlexNet](https://github.com/songhan/Deep-Compression-AlexNet)

>> - [SqueezeNet](https://github.com/DeepScale/SqueezeNet)

>> - [GoogleNet-V2](https://github.com/lim0606/caffe-googlenet-bn)

>> - [Oriented Response Networks](https://github.com/ZhouYanzhao/ORN)

>> ### 2.2 Object Detection

>> - [PVANet](https://github.com/sanghoon/pva-faster-rcnn)

>> - [R-FCN](https://github.com/Orpine/py-R-FCN)

>> - [SSD: Single Shot MultiBox Detector](https://github.com/weiliu89/caffe/tree/ssd)

>> - [YOLO in caffe](https://github.com/xingwangsfu/caffe-yolo)

>> - [DeepBox](https://github.com/weichengkuo/DeepBox)

>> - [Faster R-CNN](https://github.com/rbgirshick/py-faster-rcnn)

>> - [Fast R-CNN](https://github.com/rbgirshick/fast-rcnn)

>> ### 2.3 Image Segmentation

>> - [Mask R-CNN](https://github.com/jasjeetIM/Mask-RCNN)

>> - [DeepLab](https://bitbucket.org/aquariusjay/deeplab-public-ver2)

>> - [CRF-RNN](https://github.com/torrvision/crfasrnn)

>> - [SegNet](https://github.com/alexgkendall/caffe-segnet)

>> - [DeconvNet: Learning Deconvolution Network for Semantic Segmentation](https://github.com/HyeonwooNoh/DeconvNet)

>> - [Fully Convolutional Networks for Semantic Segmentation](https://github.com/shelhamer/fcn.berkeleyvision.org)

>> ### 2.4 Face Detection / Recognition / Verification

>> - [Center Loss](https://github.com/ydwen/caffe-face)

>> - [MTCNN_face_detection_alignment](https://github.com/DaFuCoding/MTCNN_Caffe)

>> - [VGG-Face](http://www.robots.ox.ac.uk/~vgg/software/vgg_face/)

>> - [TripletLoss(FaceNet)](https://github.com/pinguo-luhaofang/tripletloss)

>> - [dockerface](https://github.com/natanielruiz/dockerface) - Easy to install and use deep learning Faster R-CNN face detection for images and video in a docker container.

>> ### 2.5 Action Recognition

>> - [UntrimmedNets](https://github.com/wanglimin/UntrimmedNet)

>> - [C3D](https://github.com/chuckcho/video-caffe) (a recent version of Caffe)

>> - [TDD](https://github.com/wanglimin/TDD)

>> - [LRCN](https://github.com/LisaAnne/lisa-caffe-public/tree/lstm_video_deploy)

>> ### 2.6 Object Tracking

>> - [FCNT](https://github.com/scott89/FCNT)

>> ### 2.7 Scene Classification

>> - [Places CNN](http://places.csail.mit.edu/downloadCNN.html)

>> ### 2.8 Image Super-resolution

>> - [SRCNN](http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html)

>> ### 2.9 Images Generation

>> - [cnn-vis](https://github.com/jcjohnson/cnn-vis)

>> - [style-transfer](https://github.com/fzliu/style-transfer)

>> - [Colorful Image Colorization](https://github.com/richzhang/colorization)

>> - [Coupled Face Generation](https://github.com/mingyuliutw/CoGAN)

>> ### 2.10 Self-driving

>> - [DeepDrive](http://deepdrive.io/)

>> - [Berkeley DeepDrive](http://bdd.berkeley.edu/)

>> - [Princeton deepdriving](http://deepdriving.cs.princeton.edu/)

>> ### 2.11 Reinforcement Learning

>> - [DRQN](https://github.com/mhauskn/dqn)

>> - [DQN](https://github.com/muupan/dqn-in-the-caffe)

>> ## 2.12 Image Generation

>> - [VAE](https://github.com/cdoersch/vae_tutorial)

## 3. NLP

>> - [NLP-Caffe](https://github.com/Russell91/nlpcaffe)

>> - [Sentiment Analysis](http://city.shaform.com/blog/2015/06/06/caffe-sentiment-analysis.html)


## 4. Speech

>> - [Speech Recognition](https://github.com/pannous/caffe-speech-recognition)

>> - [Kaldi](https://github.com/kaldi-asr/kaldi)


## 5. Building Blocks

>> ### 5.1 Initialization

>> - [k-means initialization](https://github.com/philkr/magic_init)

>> - [LSUV](https://github.com/ducha-aiki/LSUVinit)

>> ### 5.2 Activation Function

>> TODO

## 6. Tools

>> ### 6.1 Converter

>> - [caffe-tensorflow](https://github.com/ethereon/caffe-tensorflow)

>> - [caffe-theano-conversion](https://github.com/kitofans/caffe-theano-conversion)

>> - [CaffeToKeras](https://github.com/MarcBS/keras)

>> ### 6.2 Labeling

>> - [labelme](https://github.com/wkentaro/labelme)

>> - [LabelImg](https://github.com/tzutalin/labelImg)

>> - [BBox-Label-Tool](https://github.com/puzzledqs/BBox-Label-Tool)

>> - [FastAnnotationTool](https://github.com/christopher5106/FastAnnotationTool)

>> ### 6.3 Data Augmentation

>> - [Augmentor](https://github.com/mdbloice/Augmentor)

>> ### 6.4 Parameter Search

>> - [Spearmint](https://github.com/kuz/caffe-with-spearmint)

>> ### 6.5 Visualization

>> - [netron](https://github.com/lutzroeder/netron)

>> - [deep-visualization-toolbox](https://github.com/yosinski/deep-visualization-toolbox)

>> - [DeepDraw](https://github.com/auduno/deepdraw)

>> ### 6.6 Mobile Platform

>> - [ncnn](https://github.com/Tencent/ncnn)

>> - [ShuffleNet](https://github.com/farmingyard/ShuffleNet)

>> - [caffe-android-lib](https://github.com/sh1r0/caffe-android-lib)

>> - [caffe-ios](https://github.com/aleph7/caffe/)

>> - [windows](https://github.com/dlunion/CC4.0)

>> ### 6.7 Intel and AMD

>> - [hipCaffe-AMD’s Radeon Instinct GPUs](https://github.com/ROCmSoftwarePlatform/hipCaffe)

>> - [Intel® Xeon Phi™](https://software.intel.com/en-us/articles/caffe-optimized-for-intel-architecture-applying-modern-code-techniques)

>> - [OpenCL-caffe](https://github.com/amd/OpenCL-caffe)

>> - [SkimCaffe](https://github.com/IntelLabs/SkimCaffe)

>> ### 6.8 Parallel and Distributed computing

>> - [A multi-GPU and memory-reduced MAT-Caffe](https://github.com/sciencefans/CaffeMex_v2)

>> - [SparkNet](https://github.com/amplab/SparkNet)

>> - [CaffeOnSpark](https://github.com/yahoo/CaffeOnSpark)

>> - [petuum/bosen ](https://github.com/petuum/bosen)

>> ### 6.9 Net Builder

>> - [pynetbuilder](https://github.com/jay-mahadeokar/pynetbuilder)