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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A curated list of deep learning resources for computer vision
| Date | Stars |
|---|---|
| 2026-07-31 | 11175 |
| 2026-08-01 | 11175 |
| 2026-08-03 | 11176 |
| 2026-08-06 | 11177 |
Today
+1 stars today
This week
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This month
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Momentum
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growth rate 0.00%/day
# Awesome Deep Vision [](https://github.com/sindresorhus/awesome)
A curated list of deep learning resources for computer vision, inspired by [awesome-php](https://github.com/ziadoz/awesome-php) and [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision).
Maintainers - [Jiwon Kim](https://github.com/kjw0612), [Heesoo Myeong](https://github.com/hmyeong), [Myungsub Choi](https://github.com/myungsub), [Jung Kwon Lee](https://github.com/deruci), [Taeksoo Kim](https://github.com/jazzsaxmafia)
The project is not actively maintained.
## Contributing
Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-vision/pulls) to add papers.
[](https://gitter.im/kjw0612/awesome-deep-vision?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
## Sharing
+ [Share on Twitter](http://twitter.com/home?status=http://jiwonkim.org/awesome-deep-vision%0ADeep Learning Resources for Computer Vision)
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## Table of Contents
- [Papers](#papers)
- [ImageNet Classification](#imagenet-classification)
- [Object Detection](#object-detection)
- [Object Tracking](#object-tracking)
- [Low-Level Vision](#low-level-vision)
- [Super-Resolution](#super-resolution)
- [Other Applications](#other-applications)
- [Edge Detection](#edge-detection)
- [Semantic Segmentation](#semantic-segmentation)
- [Visual Attention and Saliency](#visual-attention-and-saliency)
- [Object Recognition](#object-recognition)
- [Human Pose Estimation](#human-pose-estimation)
- [Understanding CNN](#understanding-cnn)
- [Image and Language](#image-and-language)
- [Image Captioning](#image-captioning)
- [Video Captioning](#video-captioning)
- [Question Answering](#question-answering)
- [Image Generation](#image-generation)
- [Other Topics](#other-topics)
- [Courses](#courses)
- [Books](#books)
- [Videos](#videos)
- [Software](#software)
- [Framework](#framework)
- [Applications](#applications)
- [Tutorials](#tutorials)
- [Blogs](#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](http://arxiv.org/pdf/1512.03385v1.pdf)][[Slide](http://image-net.org/challenges/talks/ilsvrc2015_deep_residual_learning_kaiminghe.pdf)]
* Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Deep Residual Learning for Image Recognition, arXiv:1512.03385.
* Microsoft (PReLu/Weight Initialization) [[Paper]](http://arxiv.org/pdf/1502.01852)
* 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]](http://arxiv.org/pdf/1502.03167)
* Sergey Ioffe, Christian Szegedy, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift, arXiv:1502.03167.
* GoogLeNet [[Paper]](http://arxiv.org/pdf/1409.4842)
* Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich, CVPR, 2015.
* VGG-Net [[Web]](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) [[Paper]](http://arxiv.org/pdf/1409.1556)
Excerpt of 47,131 characters
Read on GitHub
Jiwon Kim · SK Telecom
66
Myungsub Choi · @Tynapse · South Korea
41
20
Taeksoo Kim · Facebook · United States
9
Jung Kwon Lee · Superb AI
8
7
4
Siavash Sakhavi · AI Singapore · Singapore
4
Sven Behnke · University of Bonn
3
Amine · France
3
Zehao Huang
3
2
2
Massimiliano Patacchiola · Sapiente Education · United Arab Emirates
2
2
2
2
Gil Levi
2
trieu
2
2
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ffe045479b7a02cd, desc:computer vision