Deep Learning Reading List (Tools, Tutorials, Papers)

Deep Learning Fundamentals
R. Pieters	Python for image understanding link	A good talk for beginners
Chih-Fan Hsu, Chun-Ming Chang	手把手的深度學習實務 (slides) (labs) (github)	Great training course in Chinese, made by Data Insights Research Lab in Academia Sinica
Neural networks and deep learnings	neuralnetworksanddeeplearning.com	A very comprehensive tutorial written by Michael Nielsen
Christopher Olah	colah.github.io	A good blog to visualize NN
Geoffrey E. Hinton et al.	A fast learning algorithm for deep belief nets, Neural computation, 2006	The breakthrough paper that introduces restricted Boltzmann machines and stacked deep-belief networks
Y LeCun, Y Bengio, G Hinton	Deep Learning, Nature, 2015	Review paper written by fathers of neural networks
Deep Learning Tools
TensorFlow	www.tensorflow.org	Open source library developed by Google with C++ core and Python interface
Keras	keras.io	A wrapper for Theano and Tensorflow, very user friendly.
Theano	deeplearning.net/software/theano	DL library for Python developed by Université de Montréal
Caffe2	github.com/caffe2/caffe2	A fast and scalable C++ DL framework for visual recognition. Based on Caffe from UC Berkely
Deep Reinforcement Learning
Tambet Matiisen	Demystifying Deep Reinforcement Learning	Great introduction. Algorithms are implemented with Neon
Arhtur Juliani	Simple Reinforcement Learning with TensorFlow (Q learning)
Open AI Gym	gym.openai.com	A framework let your RL algorithms play video games
Mnih, et al.	Human-Level Control through Deep Reinforcement Learning, Nature, 2015	Deep Q-network (DQN) by Google Deep Mind (code)
David Sliver, Aja Huang et al.	Mastering the game of Go with deep neural networks and tree search, Nature 2016	Paper of AlphaGo, period.
DL for Image Classification and Object Detection
ImageNet	An image database with 14 million images organized according to the WordNet hierarchy	Hold the Large Scale Visual Recognition Challenge (ILSVRC) challenges every year
Alex Krizhevsky Ilya Sutskever Geoffrey E. Hinton	ImageNet Classification with Deep Convolutional Neural Networks, NIPS 2012	First successful deep network for image classification, aka AlexNet
Karen Simonyan, Andrew Zisserman	Very Deep Convolutional Networks for Large-Scale Image Recognition, ICLR, 2015	Winner of ILSVRC 2014
C. Szegedy et al. Google Research	Going Deeper with Convolutions, CVPR 2015	GoogLeNet
K. He et al. Microsoft Research	Deep Residual Learning for Image Recognition, CVPR 2016	CVPR 2016 best paper and winner of ILSVRC 2015, aka ResNet
DL for Image Annotations
A. Karpathy Li Fei-Fei	Deep Visual-Semantic Alignments for Generating Image Descriptions, CVPR 2015
Justin Johnson Andrej Karpathy Li Fei-Fei	DenseCap: Fully Convolutional Localization Networks for Dense Captio, CVPR 2016
DL for Video Applications (CVPR 2016)
Ting Yao et al.	Highlight Detection with Pairwise Deep Ranking for First-Person Video Summarization [pdf]
Michael Cgyli et al.	Video2GIF: Automatic Generation of Animated GIFs from Video [pdf]
B. Tekin et al.	Direct Prediction of 3D Body Poses from Motion Compensated Sequences [pdf]
Bingbing Li. et al.	Progressively Parsing Interactional Objects for Fine Grained Action Detection [pdf]
Pingbo Pan et al.	Hierarchical Recurrent Neural Encoder for Video Representation With Application to Captioning [pdf]
Zheng Shou, Dongang Wang, Shih-Fu Chang	Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs [pdf]
Ziwei Liu et al.	DeepFashion: Powering Robust Clothes Recognition and Retrieval With Rich Annotations [pdf]
Xiaofan Zhang et al.	Embedding Label Structures for Fine-Grained Feature Representation [pdf]
Other Video Applications (CVPR 2016)
Jingjing Meng et al.	From Keyframes to Key Objects: Video Summarization by Representative Object Proposal Selection [pdf]
K.  Grauman et al.	Summary Transfer: Exemplar-based Subset Selection for Video Summarization [pdf]
Feng Zhou, Yuanqing Lin	Fine-Grained Image Classification by Exploring Bipartite-Graph Labels [pdf]