Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-computer-vision-resources
A curated list of awesome CV/ML resources for easy study and reference
https://github.com/tzxiang/awesome-computer-vision-resources
- [PDF - keen/Machine-learning-learning-notes) [[HandNotes]](https://github.com/Sophia-11/Machine-Learning-Notes)
- [github - book/)
- [Homepage - us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf) [[PDF-Chinese]](https://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%A8%A1%E5%BC%8F%E8%AF%86%E5%88%AB%E4%B8%8E%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0PRML_Chinese_vision.pdf) [[Algorithms_Python]](https://github.com/ctgk/PRML) [[Algorithms_Matlab]](https://prml.github.io/)
- [PDF - %E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0/machine_learning_algorithm-master)
- [github
- [ReadOnline-Chinese - Bili]](https://space.bilibili.com/209599371/channel/detail?cid=23541) [[Video-Youtube]](https://www.youtube.com/playlist?list=PLLbeS1kM6teJqdFzw1ICHfa4a1y0hg8Ax)
- [github
- [github
- [github - into-DL-PyTorch/#/) [[PDF]](https://github.com/tzxiang/AwesomeCV/tree/master/Docs/Dive-into-DL-PyTorch.pdf)
- [Online - into-DL-TensorFlow2.0)
- [Others
- [Homepage - Chinese]](https://github.com/deeplearning-ai/machine-learning-yearning-cn) [[ReadOnline]](https://deeplearning-ai.github.io/machine-learning-yearning-cn/docs/home/) [[PDF]](https://github.com/tzxiang/AwesomeCV/tree/master/Docs/MLYearning-zh-cn.pdf)
- [Homepage - book.pdf)
- [ReadOnline - in-Action/gans-in-action)
- [ReadOnline - Chinese]](https://tigerneil.gitbooks.io/neural-networks-and-deep-learning-zh/content/index.html)
- [github
- [Homepage&PDF
- [Online
- [Online
- [Homepage - Deep-Learning)
- [Online
- [Codes
- [Homepage
- [Homepage
- [Slides - Youtube]](https://www.youtube.com/playlist?list=PLJV_el3uVTsPy9oCRY30oBPNLCo89yu49) [[Video-Bili]](https://www.bilibili.com/video/av10590361?from=search&seid=3550588589314000309) [[Notes]](https://github.com/datawhalechina/leeml-notes)
- [github
- [CoursePage - zLfQRF3EO8sYv) [[Slides]](http://cs231n.stanford.edu/syllabus.html) [[Notes]](http://cs231n.github.io/) [[Notes-Chinese]](https://zhuanlan.zhihu.com/p/21930884) [[One Class Project-VideoObSeg]](https://arxiv.org/abs/1905.07826)
- [CoursePage - Chinese]](http://www.ai-start.com/dl2017/) [[Notes2]](https://github.com/fengdu78/deeplearning_ai_books) [[Homepage1]](https://www.learndatasci.com/out/coursera-machine-learning/) [[Homepage2]](https://www.learndatasci.com/out/coursera-deep-learning-specialization/)
- [CoursePage - from-coursera-deep-learning-courses-by-andrew-ng)
- [Homepage - Field)
- [CoursePage - rwp5__7C0oIVt26ZgjG9NI) [[CourseCode]](https://github.com/aamini/introtodeeplearning_labs/)
- [CoursePage
- [Cheatsheet - git]](https://github.com/shervinea/cheatsheet-translation)
- [CoursePage
- [CoursePage
- [CoursePage
- [CoursePage
- [Homepage&Slides
- [Homepage
- [Video - View_Geometry.pdf)
- [Video
- [Video - Lyu/TensorFLow-Learning)
- [Vedio
- 人工智能的现状、任务、架构与统一,朱松纯
- 中国人工智能40年, 蔡自兴, 2016
- colah's blog
- [Homepage
- Everything You Need to Know to Reproduce SOTA Deep Learning Models
- From Image Restoration to Enhancement and Beyond
- Global Optimization for Geometric Understanding with Provable Guarantees
- Interpretable Machine Learning for Computer Vision
- Understanding Color and the In-Camera Image Processing Pipeline for Computer Vision
- Holistic 3D Reconstruction: Learning to Reconstruct Holistic 3D Structures from Sensorial Data
- Visual Recognition for Images, Video, and 3D
- Large-Scale Visual Place Recognition and Image-Based Localization
- Accelerating Computer Vision with Mixed Precision, - Yu Liu (NVIDIA)
- 3D Deep Learning and Applications in Autonomous Driving
- Second- and Higher-order Representations in Computer Vision
- Visual Learning with Limited Labeled Data
- [HomePage
- [Page
- [Page
- [Page
- [Slides
- [Homepage&Slides
- [Homepage$Slides
- [Slides
- Report
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- Blog
- [Page
- [Homepage - Version]](https://github.com/MLEveryday/100-Days-Of-ML-Code). 100 Days of Machine Learning Coding as proposed by Siraj Raval.
- [Page
- [github
- [Homepage
- [Page
- [Page
- [Page
- Some basic concept - magical-bayesian-method/) [Receptive field](https://mp.weixin.qq.com/s/NdqZk3yWVLtszGYaEAphEA)
- 线性回归
- Blog
- DeepLearning-500-questions
- 理解CNN、CNN可视化 CNN-Visualization
- [Slides
- [Homepage
- [Slides
- [Page
- [github
- [Homepage - Chinese]](https://mp.weixin.qq.com/s/VtGpQdB-swz0EhqfQQxrpA)
- [Page
- [Page
- [Page
- 一张图了解深度学习的前世今生
- An overview of gradient descent optimization algorithms
- 构建深度神经网络,我有20条「不成熟」的小建议
- 深度学习调参有哪些技巧?
- cnn结构设计技巧-兼顾速度精度与工程实现
- [Page
- [Homepage
- [Page
- [Page
- [Page
- [Page
- [Page
- [Slides
- [Page
- [Page
- [Note1 - networks/2016/11/24/convolutional-autoencoders/) [[Note3]](https://pgaleone.eu/neural-networks/deep-learning/2016/12/13/convolutional-autoencoders-in-tensorflow/)
- [Page
- [Page - related]](https://github.com/j2kun/neural-networks)
- [Homepage
- [Page
- [Page
- [PDF - tutorial) [[勘误]](https://htmlpreview.github.io/?https://github.com/jindongwang/transferlearning-tutorial/blob/master/web/transfer_tutorial.html)
- [Page - version]](https://zhuanlan.zhihu.com/p/27657264)
- [Homepage
- [Page
- [Page
- [PDF - Python_cn/OpenCV-Python-Tutorial-zh-ch.pdf)
- [Homepage
- [Homepage
- [Page
- [Page
- [Page
- [PySnooper-Note - github]](https://github.com/cool-RR/PySnooper) [[TorchSnooper-Note]](https://www.jiqizhixin.com/articles/2019-06-18-10) [[TorchSnooper-github]](https://github.com/zasdfgbnm/TorchSnooper)
- [github
- [github
- [Page
- [Page
- 30 seconds of Code - quality learning.
- Blog
- 优雅你的Python代码的15个tips
- [Homepage
- [Homepage
- [Homepage
- [example1 - CNN) [[example3]](https://github.com/ElefHead/numpy-cnn) [[Blog]](https://towardsdatascience.com/convolutional-neural-networks-from-the-ground-up-c67bb41454e1)
- [Page
- [Page
- [Page
- [Page
- [ReluNote - 5zsn8loyKTJfqTDV30w) [[Overview]](https://mp.weixin.qq.com/s?__biz=MzI1NTE4NTUwOQ==&mid=2650325236&idx=1&sn=7bd8510d59ddc14e5d4036f2acaeaf8d&scene=0#wechat_redirect)
- [Page
- [DeformConv Note
- [Page
- [Page
- [Page
- [Page
- [github
- [github
- [Page
- Page
- Blog
- [Homepage
- [Page-Eng - Chinese]](https://mp.weixin.qq.com/s/c00PXpJHctdm_YEbk4NTQA)
- [Page
- [Page1 - 875nQZYRSF5YQ)
- [Page
- [Page
- [Page
- [Page
- [Page
- [Page
- [Page
- [Page
- [Blog
- [Page
- TawbaWare
- Awesome-PyTorch-Chinese
- [Page
- [Homepage
- [Homepage
- [Page
- [Intro - OpCounter)
- [Page1
- [Page
- [Page
- [github
- [Page
- [Page
- [Page
- [Page
- [github
- [Page
- [github - AI101Edu.pdf)
- [github
- [Page1 - 164509/)
- labelme
- labelImg
- Curve-GCN
- Polygon-RNN++
- [github
- [github
- [github
- [Homepage
- [github
- [github
- [github
- MRLabeler - etc dataset, depending on OpenCV.
- [github
- [github
- Blog
- [Homepage
- [github
- [Homepage
- [Homepage
- [Matlab
- [Homepage
- BoofCV
- [Code - started-with-map-tk-for-aerial-photogrammetry/)
- [Homepage
- [Homepage
- [Page - open-source-framework-for.html) [[Intro]](https://mp.weixin.qq.com/s/3nl_IIEbk_8y1wjwD4x4cQ)
- [github
- Model Zoo: Discover open source deep learning code and pretrained models
- [github
- [github
- [github
- [github
- [github
- [github
- [github
- [Homepage
- [github
- [github
- [github
- [PDF - training-giant-neural-nets-using-pipeline-parallelism/)
- [github
- [Docs
- [github
- [github
- [Page
- [github
- [github
- [github
- [github
- [github
- [github
- Tensorflow Project Template
- [github
- [github
- [github
- [github
- Intro
- [github - recognition-iccv19/)
- [github
- [Homepage
- [Homepage - Lab)
- [Homepage
- [Homepage
- [Docs
- [github
- [github
- [github
- [github
- [github
- [github
- libfacedetection
- face.evoLVe - Performance Face Recognition Library based on PyTorch
- [github
- [NCNN Version - MNN) [[OpenVINO]](https://github.com/SyGoing/LFFD-OpenVINO)
- [github
- [github
- [github
- [github
- 利用OpenCV和Tesseract实现OCR和文本识别
- [github
- PSPNet - net.org/challenges/LSVRC/2016/results), [LSUN Semantic Segmentation Challenge 2017 @CVPR17](https://blog.mapillary.com/product/2017/06/13/lsun-challenge.html)and [WAD Drivable Area Segmentation Challenge 2018 @CVPR18](https://bdd-data.berkeley.edu/wad-2018.html). Sample experimented datasets are [ADE20K](http://sceneparsing.csail.mit.edu/), [PASCAL VOC 2012](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6) and [Cityscapes](https://www.cityscapes-dataset.com/).
- [github
- [github
- [github
- Intro
- [Homepage
- [page
- PCL: Point Cloud Library
- Libicp - asl/libpointmatcher) , [g-icp](https://github.com/avsegal/gicp) , [n-icp](http://jacoposerafin.com/nicp/)
- [github - g)
- [github
- [github
- **Exiv2**
- [github
- [github
- [Homepage
- **OpenPCDet** - H57WHvMuA)
- [github
- [github
- [Link
- [Code - started-with-map-tk-for-aerial-photogrammetry/)
- homepage
- [github
- [Homepage
- **fitlog**
- [Page
- [github - explainer/)
- awesome-machine-learning repo
- Mikoto10032/DeepLearning
- 3D Machine Learning
- Deep vision
- Awesome computer vision
- Collection of Papers for Image/Video Super-resolution
- AI Learning repo
- awesome-local-global-descriptor
- 3D-Machine-Learning
- awesome-scene-strcuture-understanding
- DeepLearningAnimePapers
- Nightmare
- Deep Dream Generator
- Detection based on MTCNN and LPRNet - Plate-Detect-Recognition-via-Deep-Neural-Networks-accuracy-up-to-99.9)
- [Proj
- [Proj - time-3d-object-detection-on-mobile.html)
- [Blog
- [Proj
- [Page
- Google Dataset Search Engine
- CVonline: Image Databases
- [Page
- [Homepage
- [Page
- [Homepage
- [Homepage
- [Homepage
- [github
- [Dataset - action.org/)
- [Dataset
- [Dataset
- [Dataset
- [Dataset
- [github
- [Dataset
- [Dataset
- [Dataset
- [Dataset
- [Dataset
- [Dataset - tracking)
- [Dataset
- [Dataset - Color-128]](https://github.com/lukaswals/unified_tracking_benchmark)
- [Dataset
- [Homepage - CL)
- [Homepage - CL)
- [Homepage
- [Page
- [Homepage
Programming Languages
Keywords
deep-learning
31
machine-learning
26
pytorch
17
computer-vision
14
python
12
tensorflow
11
cnn
6
nlp
6
neural-network
6
natural-language-processing
6
book
6
deeplearning
5
neural-networks
5
awesome
4
data-science
4
object-detection
4
jupyter-notebook
4
machinelearning
3
lstm
3
machine-learning-algorithms
3
android
3
slam
3
c-plus-plus
3
artificial-intelligence
3
cv
3
classification
2
semantic-segmentation
2
feature-engineering
2
pytorch-tutorials
2
3d-reconstruction
2
papers
2
robotics
2
awesome-list
2
visualization
2
ai
2
point-cloud
2
automl
2
resnet
2
crowd-analysis
2
crowd-counting
2
automated-machine-learning
2
keras
2
onnx
2
super-resolution
2
convolutional-neural-networks
2
dnn
2
label
2
image-segmentation
2
pretrained
2
image-annotation
2