Please check the wiki page for the latest version. Below is a backup.
Source:
Awesome deep vision: https://github.com/kjw0612/awesome-deep-vision
Awesome deep learning: https://github.com/ChristosChristofidis/awesome-deep-learning
Caffe model zoo: https://github.com/BVLC/caffe/wiki/Model-Zoo
MatConvNet pretrain: http://www.vlfeat.org/matconvnet/pretrained/
Facebook Hong Kong Deep Learning
CUHK IE Media lab: http://mmlab.ie.cuhk.edu.hk/index.html
CUHK EE Prof. Wang http://www.ee.cuhk.edu.hk/~xgwang/
Awesome RL: https://github.com/aikorea/awesome-rl
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Awesome deep vision:
PVANet: Real-time Object Detection: https://github.com/sanghoon/pva-faster-rcnn
You only look once(YOLO): https://github.com/pjreddie/darknet https://github.com/thtrieu/darkflow https://pjreddie.com/darknet/yolo/
R-FCN: Object Detection via Region-based Fully Convolutional Networks: https://github.com/daijifeng001/R-FCN
SSD: Single Shot MultiBox Detector: https://github.com/weiliu89/caffe/tree/ssd
Hierarchical Convolutional Features for Visual Tracking: https://github.com/jbhuang0604/CF2
Visual Tracking with Fully Convolutional Networks: https://github.com/scott89/FCNT
MDNet: Multi-Domain Convolutional Neural Network Tracker: https://github.com/HyeonseobNam/MDNet
Deep Networks for Image Super-Resolution with Sparse Prior: http://www.ifp.illinois.edu/~dingliu2/iccv15/
Image Colorization: https://github.com/richzhang/colorization
Context Encoders: Feature Learning by Inpainting: https://github.com/pathak22/context-encoder
Holistically-Nested Edge Detection: https://github.com/s9xie/hed
Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation: https://github.com/kolesman/SEC
Generating images pixel by pixel: https://github.com/kundan2510/pixelCNN
iGAN: Interactive Image Generation via Generative Adversarial Networks: https://github.com/junyanz/iGAN
neural-style: https://github.com/jcjohnson/neural-style
Caffe model zoo:
Berkeley-trained models
Network in Network model
Models from the BMVC-2014 paper "Return of the Devil in the Details: Delving Deep into Convolutional Nets"
Models used by the VGG team in ILSVRC-2014
Places-CNN model from MIT.
GoogLeNet GPU implementation from Princeton.
Fully Convolutional Networks for Semantic Segmentation (FCNs)
CaffeNet fine-tuned for Oxford flowers dataset
CNN Models for Salient Object Subitizing.
Deep Learning of Binary Hash Codes for Fast Image Retrieval
Places_CNDS_models on Scene Recognition
Models for Age and Gender Classification.
GoogLeNet_cars on car model classification
ParseNet: Looking wider to see better
SegNet and Bayesian SegNet
Conditional Random Fields as Recurrent Neural Networks
Holistically-Nested Edge Detection
CCNN: Constrained Convolutional Neural Networks for Weakly Supervised Segmentation
Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns
Facial Landmark Detection with Tweaked Convolutional Neural Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
ResNets: Deep Residual Networks from MSRA at ImageNet and COCO 2015
Pascal VOC 2012 Multilabel Classification Model
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters
Mixture DCNN
CNN Object Proposal Models for Salient Object Detection
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled
Mulimodal Compact Bilinear Pooling for VQA
Pose-Aware CNN Models (PAMs) for Face Recognition
Learning Structured Sparsity in Deep Neural Networks
Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks
Inception-BN full ImageNet model
ResFace101: ResNet-101 for Face Recognition
DeepYeast
ImageNet pre-trained models with batch normalization
ResNet-101 for regressing 3D morphable face models (3DMM) from single images
Cascaded Fully Convolutional Networks for Biomedical Image Segmentation
Deep Networks for Earth Observation
Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks
Striving for Simplicity: The All Convolutional Net
MatConvNet pretrain:
Object detection Fast R-CNN
Face recognition VGG-Face
Semantic segmentation Fully-Convolutional Networks, BVLC FCN, Torr Vision Group FCN-8s
ImageNet ILSVRC classification ResNet, GoogLeNet, VGG-VD, VGG-S,M,F, Caffe reference model, AlexNet
Hong Kong Deep Learning:
Super resolution: https://github.com/alexjc/neural-enhance
NewYork Texi data: https://github.com/toddwschneider/nyc-taxi-data
FB's visualization: https://github.com/facebookresearch/visdom
AdaptiveAttention: https://github.com/jiasenlu/AdaptiveAttention
Chinese English dialog: https://github.com/candlewill/Dialog_Corpus
Google text tokenizer: https://github.com/google/sentencepiece
FB AI environment: https://github.com/facebookresearch/CommAI-env
Road Segmentation, Car detection and Street classification: https://github.com/MarvinTeichmann/MultiNet
Faiss is a library for efficient similarity search and clustering of dense vectors. https://github.com/facebookresearch/faiss
FB word representations and sentence classification. https://github.com/facebookresearch/fastText
Generative models: https://github.com/wiseodd/generative-models
Char2Wav speech synthesis: http://josesotelo.com/speechsynthesis/
Line drawing colorizer: https://github.com/pfnet/PaintsChainer
SketchToFace: https://github.com/richliao/SketchToFace
Chinese OCR: https://deeperic.wordpress.com/2017/02/18/chinese-ocr-tensorflow/ https://github.com/deeperic/SpikeFlow
Chinese RC dataset: https://github.com/ymcui/Chinese-RC-Dataset
Learning to Discover Cross-Domain Relations with GAN: https://github.com/SKTBrain/DiscoGAN
Style transfer: https://github.com/xunhuang1995/AdaIN-style
Chat bot corpus: https://github.com/gunthercox/chatterbot-corpus
High-Resolution Image Inpainting: https://github.com/leehomyc/High-Res-Neural-Inpainting
Deep Learning Book: https://github.com/PaddlePaddle/book/
RNN tutorial: https://github.com/silicon-valley-data-science/RNN-Tutorial
photo style transfer: https://github.com/luanfujun/deep-photo-styletransfer
Pytorch tutorial: https://github.com/yunjey/pytorch-tutorial/blob/master/README.md
Generative model: https://github.com/wiseodd/generative-models
Gen lyrics: https://github.com/tifoit/encore.ai
Every can be painter: https://github.com/alexjc/neural-doodle
Learn anytime anywhere: https://alcamy.org/?ref=producthunt
Audio synthesis and style transfer: https://dmitryulyanov.github.io/audio-texture-synthesis-and-style-transfer/
Cat papers: https://github.com/junyanz/CatPapers
Zebra GAN: https://github.com/junyanz/CycleGAN
Deep 3D Representations at High Resolutions: https://github.com/griegler/octnet
SearchQA: https://github.com/nyu-dl/SearchQA
Hybrid Code Networks: https://github.com/suriyadeepan/hcn
iNaturalist Competition: https://github.com/visipedia/inat_comp
AI for Google's t-rex game: https://github.com/wagenaartje/neuraldino
Visual Chatbot: https://github.com/Cloud-CV/visual-chatbot
Recurrent Weighted Average (RWA): https://github.com/indiejoseph/tf-rwa-cell
The GAN Zoo: https://github.com/hindupuravinash/the-gan-zoo
TF Seq2Seq Chatbot: https://github.com/ml-hongkong/chatbot
Facebook PartAI: https://github.com/facebookresearch/ParlAI
2D-3D-Semantics Data: https://github.com/alexsax/2D-3D-Semantics
AIXIjs is a JavaScript demo for running General Reinforcement Learning (RL): https://github.com/aslanides/aixijs
Deep Pill Finder: https://github.com/jmbanda/healthplusplus2016
AI-Assisted Isomorphic Application Engine for Embedded: https://github.com/Artificial-Engineering/lycheejs#quickstart
Snapshot Ensemble in Keras: https://github.com/titu1994/Snapshot-Ensembles
Sketch-RNN: A Generative Model for Vector Drawings: https://github.com/tensorflow/magenta/blob/master/magenta/models/sketch_rnn/README.md
Efficient Parallel Methods for Deep Reinforcement Learning: https://github.com/Alfredvc/paac
Visual Reasoning: https://github.com/facebookresearch/clevr-iep
pixel-wise annotations for fashion images: https://github.com/lemondan/HumanParsing-Dataset
sequence-to-sequence learning toolkit for Torch: https://github.com/facebookresearch/fairseq
ResNeXt: https://github.com/facebookresearch/ResNeXt
Dataset For Music Analysis: https://github.com/mdeff/fma
TensorFlow Best Practices: https://github.com/aicodes/tf-bestpractice
Unsupervised deep learning using unlabelled videos on the web: https://github.com/pathak22/unsupervised-video
Character-Level language models: https://github.com/indiejoseph/chinese-char-rnn
code2doc: https://github.com/Avmb/code-docstring-corpus
xnor enhanced neural nets: https://github.com/hpi-xnor/BMXNet/blob/master/README.md
Deep generative models, variational inference: https://github.com/blei-lab/edward
Language Modeling: https://github.com/okuchaiev/f-lm
Awesome Figures of Neural Networks: https://github.com/aonotas/neural-figures
Image augmentation: https://github.com/aleju/imgaug
Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information: https://github.com/mwydmuch/ViZDoom
AGI??: https://github.com/WalnutiQ/wAlnut
How to Train a GAN: https://github.com/soumith/ganhacks
End-to-End Learning for Negotiation Dialogues: https://github.com/facebookresearch/end-to-end-negotiator
Video Imagination from a Single Image: https://github.com/gitpub327/VideoImagination
Facebook bAbI dataset 10k: https://github.com/ml-hongkong/resources/blob/master/babi.md
stock2vec: https://github.com/ml-hongkong/stock2vec
Pytorch-Sketch-RNN: https://github.com/alexis-jacq/Pytorch-Sketch-RNN
基于多搜索引擎和深度学习技术的自动问答: https://github.com/SnakeHacker/QA-Snake
DeepLearningFlappyBird: https://github.com/yenchenlin/DeepLearningFlappyBird
Action Recognition using Visual Attention: https://github.com/kracwarlock/action-recognition-visual-attention
µniverse: RL environments for HTML5 games: https://github.com/unixpickle/muniverse
MobileID: Face Model Compression by Distilling Knowledge from Neurons: https://github.com/liuziwei7/mobile-id
Unsupervised Image to Image Translation with GAN: https://github.com/zsdonghao/Unsup-Im2Im
Dual Path Networks: https://github.com/cypw/DPNs
Essential Cheat Sheets: https://github.com/kailashahirwar/cheatsheets-ai
sentence embeddings: https://github.com/facebookresearch/InferSent
Pointer networks: https://github.com/zygmuntz/pointer-networks-experiments
Recurrent Additive Networks (RAN): https://github.com/indiejoseph/tf-ran-cell
Iterative Pruning: https://github.com/garion9013/impl-pruning-TF
Tensorflow iOS ObjectDetection: https://github.com/JieHe96/iOS_Tensorflow_ObjectDetection_Example
Deep Value Network: https://github.com/gyglim/dvn
Recurrent Neural Networks Tutorial: https://github.com/silicon-valley-data-science/RNN-Tutorial
Stock Trading: https://github.com/kh-kim/stock_market_reinforcement_learning
FeUdal Networks: https://github.com/dmakian/feudal_networks
Visual Dialog: https://github.com/batra-mlp-lab/visdial
Image classification with synthetic gradient: https://github.com/vyraun/DNI-tensorflow
Visualizations for machine learning datasets: https://github.com/pair-code/facets
Tensorflow implementation of the SRGAN: https://github.com/brade31919/SRGAN-tensorflow
Relational Networks and a VQA: https://github.com/gitlimlab/Relation-Network-Tensorflow
Relational Networks: https://github.com/kimhc6028/relational-networks
evaluating reinforcement learning algorithms: https://github.com/rll/rllab
training RL systems from John Schulman's lecture: https://github.com/williamFalcon/DeepRLHacks
Poincaré Embedding: https://github.com/TatsuyaShirakawa/poincare-embedding
Collection of generative models: https://github.com/hwalsuklee/tensorflow-generative-model-collections
five video classification methods: https://github.com/harvitronix/five-video-classification-methods
Chinese Named Entity Recognition: https://github.com/crownpku/Information-Extraction-Chinese
Face Data Augmentation: https://github.com/iacopomasi/face_specific_augm
Video Object Segmentation: https://github.com/scaelles/OSVOS-TensorFlow
OpenData in insurance: https://github.com/Samurais/insuranceqa-corpus-zh
Image augmentation: https://github.com/mdbloice/Augmentor
transformation-invariant pooling: https://github.com/dlaptev/TI-pooling
TensorFlow tutorials and best practices: https://github.com/vahidk/EffectiveTensorflow
A TensorBoard plugin for visualizing arbitrary tensors: https://github.com/chrisranderson/beholder
A Deep Learning toolkit based on iOS: https://github.com/amazingyyc/Brouhaha
pyTorch: https://github.com/marcoleewow/Find-Optimal-Space-Embedding-for-Trees
StarCraft II Learning Environment: https://github.com/deepmind/pysc2
Google's Tacotron: https://github.com/barronalex/Tacotron
Photographic Image Synthesis: https://github.com/CQFIO/PhotographicImageSynthesis
learning by association: https://github.com/haeusser/learning_by_association
neural network for the mobile platform: https://github.com/Tencent/ncnn
Game Agent Framework: https://github.com/SerpentAI/SerpentAI
Reinforcement learning environments with musculoskeletal: https://github.com/stanfordnmbl/osim-rl
Automatic Image Cropping: https://github.com/wuhuikai/TF-A2RL
any TensorFlow model in a single line: https://github.com/ajbouh/tfi
TensorFlow Agents: https://github.com/tensorflow/agents
book "Deep Learning with Python": https://github.com/fchollet/deep-learning-with-python-notebooks
Tensorflow wrapper for DataFrames on Apache Spark: https://github.com/databricks/tensorframes
Lattice methods in TensorFlow: https://github.com/tensorflow/lattice
Distributed training framework for TensorFlow: https://github.com/uber/horovod
state of the art Reinforcement Learning algorithms: https://github.com/NervanaSystems/coach
StackGAN-v2: https://github.com/hanzhanggit/StackGAN-v2
Progressive Growing of GANs for Improved Quality: https://github.com/tkarras/progressive_growing_of_gans
two-level RCN model: https://github.com/vicariousinc/science_rcn
Synthetic Gradients for PyTorch: https://github.com/koz4k/dni-pytorch
DiracNets: https://github.com/szagoruyko/diracnets/blob/master/README.md
make Ascii Art by Deep Learing: https://github.com/OsciiArt/DeepAA
CondenseNet: Light weighted CNN for mobile devices: https://github.com/ShichenLiu/CondenseNet
GAN Timeline: https://github.com/dongb5/GAN-Timeline/blob/master/README.md
Uber's genetic algorithm for RL: https://github.com/unixpickle/uber-ga
Naive Bayes implementation with digit recognition: https://github.com/r9y9/naive_bayes
corpus of Chinese abbreviation: https://github.com/lancopku/Chinese-abbreviation-dataset
style2paints: https://github.com/lllyasviel/style2paints/blob/master/README.md
FAIR's Mask R-CNN and RetinaNet: https://github.com/facebookresearch/Detectron
Learning embeddings for classification: https://github.com/facebookresearch/StarSpace
Adversarial Examples for Evaluating Reading Comprehension Systems: https://github.com/robinjia/adversarial-squad
Automatic Training of MCMC Samplers: https://github.com/brain-research/l2hmc
A3C PyTorch: https://github.com/dgriff777/a3c_continuous
Poincare embedding: https://github.com/facebookresearch/poincare-embeddings
Dynamic_Neural_Manifold: https://github.com/Miej/Dynamic_Neural_Manifold
GAN for Photorealistic and Identity: https://github.com/HRLTY/TP-GAN
CipherGAN: https://github.com/for-ai/CipherGAN
Benchmarks and Temporal Convolutional Networks: https://github.com/locuslab/TCN
Multilingual Unsupervised or Supervised word Embeddings: https://github.com/facebookresearch/MUSE#ground-truth-bilingual-dictionaries
SpaceX Falcon 9: https://github.com/arex18/rocket-lander
Chinese Word Vectors: https://github.com/Embedding/Chinese-Word-Vectors
Deep Painterly Harmonization: https://github.com/luanfujun/deep-painterly-harmonization
Augmented Random Search: https://github.com/modestyachts/ARS
Learning-to-See-in-the-Dark: https://github.com/cchen156/Learning-to-See-in-the-Dark
Music database: https://github.com/chrisdonahue/nesmdb
Fast deep net: https://github.com/mitdbg/fastdeepnets
gradient-checkpointing: https://github.com/openai/gradient-checkpointing
Full World Models Implementation: https://github.com/AdeelMufti/WorldModels
State of the art: https://paperswithcode.com/sota?fbclid=IwAR1Rdpnx2Uazou_3gnzOcfYhq1zOlfW6W9RngR2hl42ND1KOl9nKqT0Ij-U
CUHK IE Media lab:
Deep Fashion: http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion.html
Others:
Openface: https://cmusatyalab.github.io/openface/
dlib c++: http://blog.dlib.net/2014/08/real-time-face-pose-estimation.html
Age and gender: http://www.openu.ac.il/home/hassner/projects/cnn_agegender/ https://gist.github.com/GilLevi/c9e99062283c719c03de
OCR: https://github.com/ayman/textr
Chinese front generation: https://github.com/kaonashi-tyc/Rewrite
Deep Learning Face Detection: https://github.com/guoyilin/FaceDetection_CNN
simple GAN: https://github.com/kvfrans/generative-adversial
simple Variational autoencoder: https://github.com/kvfrans/variational-autoencoder
Nvidia pix2pix: https://github.com/NVIDIA/pix2pixHD