# 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 - [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) - [Datasets](#Datasets) # 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) # 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) - [Machine Learning Problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems) - [Gradient Boosting](https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers) - [Decision Tree](https://github.com/benedekrozemberczki/awesome-decision-tree-papers) # 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) - [Deep Learning for Graphs](https://github.com/DeepGraphLearning/LiteratureDL4Graph) - [Real-time Network](https://github.com/wpf535236337/real-time-network) - [Deep Learning Interpretability](https://github.com/oneTaken/awesome_deep_learning_interpretability) # 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) - [DeepFakes](https://github.com/datamllab/awesome-deepfakes-materials) - [Event-based Vision Resources](https://github.com/uzh-rpg/event-based_vision_resources) - Research Topics - [Action Recognition](https://github.com/jinwchoi/awesome-action-recognition) - [Colorization](https://github.com/MarkMoHR/Awesome-Image-Colorization) - [Image Classification](https://github.com/weiaicunzai/awesome-image-classification) - [imgclsmob](https://github.com/osmr/imgclsmob) - [Image Registration](https://github.com/Awesome-Image-Registration-Organization/awesome-image-registration) - Object Detection - [amusi/Object Detection](https://github.com/amusi/awesome-object-detection) - [hoya012/Object Detection]( https://github.com/hoya012/deep_learning_object_detection ) - [Tiny Object Detection](https://github.com/kuanhungchen/awesome-tiny-object-detection) - [Small Object Detection](https://github.com/tjtum-chenlab/SmallObjectDetectionList) - [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) - [Face Landmark Detection](https://github.com/mrgloom/Face-landmarks-detection-benchmark) - [Landmark Detection](https://github.com/D-X-Y/landmark-detection) - [Gaze Estimation](https://github.com/WuZhuoran/awesome-gaze) - Image Segmentation - [Semantic Segmentation](https://github.com/mrgloom/awesome-semantic-segmentation) - [Segmentation.X](https://github.com/wutianyiRosun/Segmentation.X) - [Panoptic Segmentation](https://github.com/Angzz/awesome-panoptic-segmentation) - [Weakly Supervised Semantic Segmentation](https://github.com/JackieZhangdx/WeakSupervisedSegmentationList) - [Referring Image Segmentation](https://github.com/MarkMoHR/Awesome-Referring-Image-Segmentation) - [Object Tracking](https://github.com/foolwood/benchmark_results) - [Visual Tracking1](https://github.com/foolwood/benchmark_results) - [Visual Tracking2](https://github.com/czla/daily-paper-visual-tracking) - [Multi-Object Tracking](https://github.com/SpyderXu/multi-object-tracking-paper-list) - [Tracking and Detection](https://github.com/abhineet123/Deep-Learning-for-Tracking-and-Detection) - [daily-paper-visual-tracking](https://github.com/czla/daily-paper-visual-tracking) - [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) - [Human Motion](https://github.com/derikon/awesome-human-motion) - [Human-Object Interaction(HOI)](https://github.com/DirtyHarryLYL/HOI-Learning-List) - 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) - [Text Detection and Recognition](https://github.com/hwalsuklee/awesome-deep-text-detection-recognition) - [Scene Text Recognition Resources](https://github.com/HCIILAB/Scene-Text-Recognition) - Super Resolution - [Super Resolution (ChaofWang)](https://github.com/ChaofWang/Awesome-Super-Resolution) - [Super Resolution (ptkin)]() - [Image Super Resolution](https://github.com/YapengTian/Single-Image-Super-Resolution) - [Video Super Resolution](https://github.com/LoSealL/VideoSuperResolution) - 3D - [3D Reconstruction](https://github.com/openMVG/awesome_3DReconstruction_list) - [OCR](https://github.com/kba/awesome-ocr) - Re-ID - [Person Re-ID(1)](https://github.com/bismex/Awesome-person-re-identification) - [Person Re-ID(2)](https://github.com/FDU-VTS/Awesome-Person-Re-Identification) - [Vehicle Re-ID(1)](https://github.com/layumi/Vehicle_reID-Collection) - [Vehicle Re-ID(2)](https://github.com/knwng/awesome-vehicle-re-identification) - [Pedestrian Attribute Recognition](https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List) - [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) - [Low Lignt Enhancement](https://github.com/Elin24/Awesome-Low-Lignt-Enhancement) - 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) - [Medical Image Segmentation](https://github.com/JunMa11/SOTA-MedSeg) - [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 and Video Denoising](https://github.com/z-bingo/awesome-image-denoising-state-of-the-art) - [Image Deraining](https://github.com/nnUyi/DerainZoo) - [Image/Video Deblurring]( https://github.com/subeeshvasu/Awesome-Deblurring ) - Image to Image(img2img) - [lzhbrian/Image to Image](https://github.com/lzhbrian/image-to-image-papers) - [xiaweihao/Image to Image](https://github.com/xiaweihao/awesome-image-translation) - [Video Analysis](https://github.com/HuaizhengZhang/Awsome-Deep-Learning-for-Video-Analysis) - [Video Object Segmentation(VOS)](https://github.com/du0915/Video-Object-Segmentation-Paper-List) - [Edge Detection]() - [Local and Global Descriptor](https://github.com/shamangary/awesome-local-global-descriptor) - Salience - [Salient Object Detection(SOD)](https://github.com/jiwei0921/SOD-CNNs-based-code-summary-) - [Saliency Detection & Segmentation](https://github.com/lartpang/awesome-segmentation-saliency-dataset#another-awesome-dataset-list) - [Fashion + AI](https://github.com/lzhbrian/Cool-Fashion-Papers) - [Event-based Vision Resources](https://github.com/uzh-rpg/event-based_vision_resources) # 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) - [NLP Paper](https://github.com/changwookjun/nlp-paper) - [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) - Research Topics - [Machine Translation](https://github.com/ZNLP/SOTA-MT) # 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) # Other Research Topics - Bayesian - [Bayesian](https://github.com/dimenwarper/awesome-bayes) - [Deep Bayesian](https://github.com/otokonoko8/deep-Bayesian-nonparametrics-papers) - [Capsule Networks](https://github.com/sekwiatkowski/awesome-capsule-networks) - [Data Augmentation](https://github.com/AgaMiko/data-augmentation-review) - [Emebedded AI](https://github.com/ysh329/awesome-embedded-ai) - 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) - [SLAM List](https://github.com/OpenSLAM/awesome-SLAM-list) - [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) - [SFM-Visual-SLAM](https://github.com/marknabil/SFM-Visual-SLAM) - [SLAM Resources](https://github.com/ckddls1321/SLAM_Resources) - [Graph Neural Networks(GNN)](https://github.com/thunlp/GNNPapers) - [Reinforcement Learning](https://github.com/aikorea/awesome-rl) - [Implementation of Reinforcement Learning Algorithms](https://github.com/dennybritz/reinforcement-learning) - [Reinforcement Learning Chinese](https://github.com/wwxFromTju/awesome-reinforcement-learning-zh):中文整理的强化学习资料 - [Transfer Learning](https://github.com/jindongwang/transferlearning) - [Trajectory Prediction](https://github.com/jiachenli94/Awesome-Interaction-aware-Trajectory-Prediction) - [Zero-Shot Learning](https://github.com/chichilicious/awesome-zero-shot-learning) - Few-Shot Learning - [Duan-JM/Few-Shot Learning](https://github.com/Duan-JM/awesome-papers-fewshot) - [e-271/Few-Shot Learning](https://github.com/e-271/awesome-few-shot-learning) - Federated Learning - [poga/Federated Learning](https://github.com/poga/awesome-federated-learning) - [Federated Computing/Learning](https://github.com/tushar-semwal/awesome-federated-computing) - Meta-Learning - [Meta-Learning1](https://github.com/dragen1860/awesome-meta-learning) - [Meta-Learning2](https://github.com/sudharsan13296/Awesome-Meta-Learning) - [Open Set Recognition](https://github.com/iCGY96/awesome_OpenSetRecognition_list) - Self-Supervised - [jason718/Self-Supervised](https://github.com/jason718/awesome-self-supervised-learning) - [Sungman-Cho/Self-Supervised]( https://github.com/Sungman-Cho/Awesome-Self-Supervised-Papers ) - [Graph Classification](https://github.com/benedekrozemberczki/awesome-graph-classification) - [Incremental Learning](https://github.com/xialeiliu/Awesome-Incremental-Learning) - [AutoML](https://github.com/hibayesian/awesome-automl-papers) - [AutoML Survey](https://github.com/DataSystemsGroupUT/AutoML_Survey) - [AutoML-and-Lightweight-Models](https://github.com/guan-yuan/awesome-AutoML-and-Lightweight-Models) - [NAS](https://github.com/D-X-Y/Awesome-NAS) - [Architecture Search](https://github.com/markdtw/awesome-architecture-search) - [LITERATURE ON NEURAL ARCHITECTURE SEARCH](https://www.automl.org/automl/literature-on-neural-architecture-search/) - [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) - [Neural Network Pruning](https://github.com/he-y/Awesome-Pruning) - [Binary Neural Networks](https://github.com/michaeltinsley/awesome-binary-neural-networks) - [Multimodal Research](https://github.com/Eurus-Holmes/Awesome-Multimodal-Research) - [Multimodal Machine Learning](https://github.com/pliang279/awesome-multimodal-ml) - [Neural Rendering](https://github.com/xiaweihao/awesome-neural-rendering) - [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 - [Autonomous Vehicles](https://github.com/takeitallsource/awesome-autonomous-vehicles) - [Autonomous Vehicles-CH]( https://github.com/DeepTecher/awesome-autonomous-vehicle ) - [Lidar Point cloud processing for Autonomous Driving](https://github.com/beedotkiran/Lidar_For_AD_references) - [Anomaly Detection](https://github.com/yzhao062/anomaly-detection-resources) - [Point Cloud Analysis](https://github.com/Yochengliu/awesome-point-cloud-analysis) - [3D Point Clouds](https://github.com/QingyongHu/SoTA-Point-Cloud) - [Affective_Computing](https://github.com/suzana-ilic/Deep_Learning_Affective_Computing) - Knowledge Distillation - [Knowledge Distillation(dkozlov)](https://github.com/dkozlov/awesome-knowledge-distillation) - [Knowledge Distillation(FLHonker)](https://github.com/FLHonker/Awesome-Knowledge-Distillation) - [Click-Through Rate Prediction](https://github.com/shenweichen/DeepCTR) - [VAE](https://github.com/matthewvowels1/Awesome-VAEs) - [Imbalanced Learning](https://github.com/ZhiningLiu1998/awesome-imbalanced-learning) # 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) # Framework - [TensorFlow](https://github.com/jtoy/awesome-tensorflow) - [TensorFlow From Zero To- One](https://github.com/amusi/TensorFlow-From-Zero-To-One) - [TensorFlow Lite](https://github.com/margaretmz/awesome-tflite) - [PyTorch](https://github.com/bharathgs/Awesome-pytorch-list) - [PyTorch From Zero To- One](https://github.com/amusi/PyTorch-From-Zero-To-One) - [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) # Datasets - [Segmentation & Saliency detection](https://github.com/lartpang/awesome-segmentation-saliency-dataset)