Awesome Deep Vision

A curated list of deep learning resources for computer vision, inspired by awesome-php and awesome-computer-vision.

Maintainers - Jiwon Kim, Heesoo Myeong, Myungsub Choi, Jung Kwon Lee, Taeksoo Kim

The project is not actively maintained.

Contributing

Please feel free to pull requests to add papers.

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Table of Contents

• Papers
• ImageNet Classification
• Object Detection
• Object Tracking
• Low-Level Vision
  • Super-Resolution
  • Other Applications
• Edge Detection
• Semantic Segmentation
• Visual Attention and Saliency
• Object Recognition
• Human Pose Estimation
• Understanding CNN
• Image and Language
  • Image Captioning
  • Video Captioning
  • Question Answering
• Image Generation
• Other Topics
• Courses
• Books
• Videos
• Software
• Framework
• Applications
• Tutorials
• Blogs

Papers

ImageNet Classification

(from Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton, ImageNet Classification with Deep Convolutional Neural Networks, NIPS, 2012.) * Microsoft (Deep Residual Learning) [Paper][Slide] * Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Deep Residual Learning for Image Recognition, arXiv:1512.03385. * Microsoft (PReLu/Weight Initialization) [Paper] * Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification, arXiv:1502.01852. * Batch Normalization [Paper] * Sergey Ioffe, Christian Szegedy, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift, arXiv:1502.03167. * GoogLeNet [Paper] * Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich, CVPR, 2015. * VGG-Net [Web] [Paper] * Karen Simonyan and Andrew Zisserman, Very Deep Convolutional Networks for Large-Scale Visual Recognition, ICLR, 2015. * AlexNet [Paper] * Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton, ImageNet Classification with Deep Convolutional Neural Networks, NIPS, 2012.

Object Detection

(from Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, arXiv:1506.01497.)

• PVANET [Paper] [Code]
• Kye-Hyeon Kim, Sanghoon Hong, Byungseok Roh, Yeongjae Cheon, Minje Park, PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection, arXiv:1608.08021
• OverFeat, NYU [Paper]
• OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks, ICLR, 2014.