awesome-ai-awesomeness/README.md

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# Awesome AI Awesomeness
A curated list of awesome awesomeness about artificial intelligence(AI).
If you want to contribute to this list (please do), send me a pull request.
# Table of Contents
<!-- MarkdownTOC depth=4 -->
- [Artificial Intelligence(AI)](#AI)
- [Machine Learning(ML)](#ML)
- [Deep Learning(DL)](#DL)
- [Computer Vision(CV)](#CV)
- [Natural Language Processing(NLP)](#NLP)
- [Speech Recognition](#SR)
- [Other Research Topics](#ORT)
- [Programming Languages](#PL)
- [Framework](#Framework)
<a name="AI"></a>
# Artificial Intelligence(AI)
- [AI](https://github.com/owainlewis/awesome-artificial-intelligence)
- [AI-Use-Cases](https://github.com/faktionai/awesome-ai-usecases)
- [AI residency programs information](https://github.com/ankitshah009/all-about-ai-residency)
<a name="ML"></a>
# Machine Learning(ML)
- [ML](https://github.com/josephmisiti/awesome-machine-learning)
- [ML-Source-Code](https://github.com/src-d/awesome-machine-learning-on-source-code)
- [ML-CN](https://github.com/jobbole/awesome-machine-learning-cn)
- [Adversarial-ML](https://github.com/yenchenlin/awesome-adversarial-machine-learning)
- [Quantum-ML](https://github.com/krishnakumarsekar/awesome-quantum-machine-learning)
- [3D-Machine-Learning](https://github.com/timzhang642/3D-Machine-Learning)
- [Machine Learning Interpretability](https://github.com/jphall663/awesome-machine-learning-interpretability)
- [Machine Learning System](https://github.com/HuaizhengZhang/Awesome-System-for-Machine-Learning)
- [Mobile Machine Learning](https://github.com/fritzlabs/Awesome-Mobile-Machine-Learning)
<a name="DL"></a>
# Deep Learning(DL)
- [DL](https://github.com/ChristosChristofidis/awesome-deep-learning)
- [DL-Papers](https://github.com/terryum/awesome-deep-learning-papers)
- [DL-Resources](https://github.com/guillaume-chevalier/Awesome-Deep-Learning-Resources)
- [DeepLearning-500-questions](https://github.com/scutan90/DeepLearning-500-questions)
- [Deep-Learning-in-Production](https://github.com/ahkarami/Deep-Learning-in-Production)
- [DNN Compression and Acceleration](https://github.com/MingSun-Tse/EfficientDNNs)
- [Architecture Search](https://github.com/markdtw/awesome-architecture-search)
<a name="CV"></a>
# Computer Vision(CV)
- [CV](https://github.com/jbhuang0604/awesome-computer-vision)
- [CV2](https://github.com/kjw0612/awesome-deep-vision)
- [CV-People](Awesome-People-in-Computer-Vision)
- Research Topics
- [Image Classification](https://github.com/weiaicunzai/awesome-image-classification)
- [imgclsmob](https://github.com/osmr/imgclsmob)
- [Object Detection](https://github.com/amusi/awesome-object-detection)
- [Video Object Detection](https://github.com/huanglianghua/video-detection-paper-list)
- Face
- [Face Detection & Recognition](https://github.com/ChanChiChoi/awesome-Face_Recognition)
- [awesome-face](https://github.com/polarisZhao/awesome-face)
- [Facial Expression Recognition (FER)](https://github.com/EvelynFan/AWESOME-FER)
- Image Segmentation
- [Semantic Segmentation](https://github.com/mrgloom/awesome-semantic-segmentation)
- [Segmentation.X](https://github.com/wutianyiRosun/Segmentation.X)
- [Object Tracking](https://github.com/foolwood/benchmark_results)
- [Multi-Object Tracking](https://github.com/SpyderXu/multi-object-tracking-paper-list)
- [Pose estimation](https://github.com/wjbKimberly/pose_estimation_CVPR_ECCV_2018)
- Human Pose estimation
- [Human Pose estimation 1](https://github.com/cbsudux/awesome-human-pose-estimation)
- [Human Pose estimation 2](https://github.com/wangzheallen/awesome-human-pose-estimation)
- [Hand Pose estimation](https://github.com/xinghaochen/awesome-hand-pose-estimation)
- Scene Text
- [Scene Text Localization and Recognition](https://github.com/chongyangtao/Awesome-Scene-Text-Recognition)
- [Scene Text Localization & Recognition Resources](https://github.com/whitelok/image-text-localization-recognition)
- [Scene Text Detection and Recognition](https://github.com/Jyouhou/SceneTextPapers)
- [OCR](https://github.com/kba/awesome-ocr)
- Re-ID
- [Person Re-ID](https://github.com/bismex/Awesome-person-re-identification)
- [Vehicle Re-ID](https://github.com/knwng/awesome-vehicle-re-identification)
- [Image Captioning](https://github.com/zhjohnchan/awesome-image-captioning)
- [Question Answering](https://github.com/dapurv5/awesome-question-answering)
- [Crowd Counting](https://github.com/gjy3035/Awesome-Crowd-Counting)
- [Lane Detection](https://github.com/amusi/awesome-lane-detection)
- Image Retrieval
- [Awesome image retrieval papers (1)](https://github.com/willard-yuan/awesome-cbir-papers)
- [Awesome image retrieval papers (2)](https://github.com/lgbwust/awesome-image-retrieval-papers)
- [Medical Imaging](https://github.com/fepegar/awesome-medical-imaging)
- [Medical Data](https://github.com/beamandrew/medical-data)
- [Medical imaging datasets](https://github.com/sfikas/medical-imaging-datasets)
- [Awesome GAN for Medical Imaging](https://github.com/xinario/awesome-gan-for-medical-imaging)
- [Deep Learning for Medical Applications](https://github.com/albarqouni/Deep-Learning-for-Medical-Applications)
- [Image Inpainting](https://github.com/1900zyh/Awesome-Image-Inpainting)
- [Image Dehazing](https://github.com/youngguncho/awesome-dehazing)
- Image Denoising
- [reproducible-image-denoising-state-of-the-art](https://github.com/wenbihan/reproducible-image-denoising-state-of-the-art)
- [Image-Denoising-State-of-the-art](https://github.com/flyywh/Image-Denoising-State-of-the-art)
- [Image to Image](https://github.com/lzhbrian/image-to-image-papers)
- [Video Analysis](https://github.com/HuaizhengZhang/Awsome-Deep-Learning-for-Video-Analysis)
<a name="NLP"></a>
# Natural Language Processing(NLP)
- [NLP](https://github.com/keon/awesome-nlp)
- [NLP-progress](https://github.com/sebastianruder/NLP-progress)
- [CoreNLP](https://github.com/stanfordnlp/CoreNLP)
- [NLPIR](https://github.com/NLPIR-team/NLPIR)
- [nlp_course](https://github.com/yandexdataschool/nlp_course)
- [nlp-datasets](https://github.com/niderhoff/nlp-datasets)
- [nlp-reading-group](https://github.com/clulab/nlp-reading-group)
- [Awesome-Chinese-NLP](https://github.com/crownpku/Awesome-Chinese-NLP): 中文自然语言处理相关资料
- [awesome-dl4nlp](https://github.com/brianspiering/awesome-dl4nlp)
- [awesome-sentence-embedding](https://github.com/Separius/awesome-sentence-embedding)
<a name="SR"></a>
# Speech Recognition
- [speech_recognition](https://github.com/Uberi/speech_recognition)
- [awesome-speech-recognition-speech-synthesis-papers](https://github.com/zzw922cn/awesome-speech-recognition-speech-synthesis-papers)
<a name="ORT"></a>
# Other Research Topics
- [Capsule Networks](https://github.com/sekwiatkowski/awesome-capsule-networks)
- GAN
- [really-awesome-gan](https://github.com/nightrome/really-awesome-gan)
- [AdversarialNetsPapers](https://github.com/zhangqianhui/AdversarialNetsPapers)
- [the-gan-zoo](https://github.com/hindupuravinash/the-gan-zoo)
- [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN)
- [gans-awesome-applications](https://github.com/nashory/gans-awesome-applications): Curated list of awesome GAN applications and demo
- [SLAM](https://github.com/kanster/awesome-slam)
- [VSLAM](https://github.com/tzutalin/awesome-visual-slam)
- [SLAM(Chinese)](https://github.com/YiChenCityU/Recent_SLAM_Research)
- [SLAM Datasets](https://github.com/youngguncho/awesome-slam-datasets)
- [Reinforcement Learning](https://github.com/aikorea/awesome-rl)
- [Transfer Learning](https://github.com/jindongwang/transferlearning)
- [Zero-Shot Learning](https://github.com/chichilicious/awesome-zero-shot-learning)
- [Few-Shot Learning](https://github.com/e-271/awesome-few-shot-learning)
- [Meta-Learning](https://github.com/dragen1860/awesome-meta-learning)
- [Self-Supervised](https://github.com/jason718/awesome-self-supervised-learning)
- [Graph Embedding](https://github.com/benedekrozemberczki/awesome-graph-embedding)
- [Incremental Learning](https://github.com/xialeiliu/Awesome-Incremental-Learning)
- [AutoML](https://github.com/hibayesian/awesome-automl-papers)
- [Model Compression](https://github.com/cedrickchee/awesome-ml-model-compression)
- [EfficientDNNs](https://github.com/MingSun-Tse/EfficientDNNs)
- [Model Compression and Acceleration](https://github.com/memoiry/Awesome-model-compression-and-acceleration)
- [Domain Adaptation](https://github.com/zhaoxin94/awsome-domain-adaptation)
- [Robotics](https://github.com/kiloreux/awesome-robotics)
- [Recommender Systems](https://github.com/robi56/Deep-Learning-for-Recommendation-Systems)
- [Autonomous Vehicles](https://github.com/takeitallsource/awesome-autonomous-vehicles)
<a name="PL"></a>
# Programming Languages
- [C](https://notabug.org/koz.ross/awesome-c)
- [C++](https://github.com/fffaraz/awesome-cpp)
- [Python](https://github.com/vinta/awesome-python)
- [JAVA](https://github.com/akullpp/awesome-java)
- [JavaScript](awesome-javascript)
- [Julia](https://github.com/svaksha/Julia.jl)
- [MATLAB](https://github.com/uhub/awesome-matlab)
- [R](https://github.com/qinwf/awesome-R)
<a name="Framework"></a>
# Framework
- [TensorFlow](https://github.com/jtoy/awesome-tensorflow)
- [PyTorch](https://github.com/bharathgs/Awesome-pytorch-list)
- [Keras](https://github.com/fchollet/keras-resources)
- [MXNet](https://github.com/chinakook/Awesome-MXNet)
- [Caffe](https://github.com/MichaelXin/Awesome-Caffe)
- [Torch](https://github.com/carpedm20/awesome-torch)
- [Chainer](awesome-chainer)