Book | Links |
---|---|
Nixon, Mark, and Alberto Aguado. “Feature extraction and image processing for computer vision.” Academic press, (2019). | goodreads |
González, Rafael Corsino and Richard E. Woods. “Digital image processing, 4th Edition.” (2018). | goodreads |
Prince, Simon. “Computer Vision: Models, Learning, and Inference.” (2012). | goodreads |
Forsyth, David Alexander and Jean Ponce. “Computer Vision - A Modern Approach, Second Edition.” (2011). | goodreads |
Szeliski, Richard. “Computer Vision - Algorithms and Applications.” Texts in Computer Science (2010). | goodreads |
Bishop, Charles M.. “Pattern recognition and machine learning, 5th Edition.” Information science and statistics (2007). | goodreads |
Harltey, Andrew and Andrew Zisserman. “Multiple view geometry in computer vision (2. ed.).” (2003). | goodreads |
Stockman, George C. and Linda G. Shapiro. “Computer Vision.” (2001). | goodreads |
Course | Tags | Platform |
---|---|---|
Version Control with Git | Git |
Udacity |
Git Essential Training | Git |
LinkedIn Learning |
Learning GitHub | Git |
LinkedIn Learning |
Introduction to Python Programming | Programming |
Udacity |
Learning Python | Programming |
LinkedIn Learning |
Intro to Data Science | Data Science |
Udacity |
Intro to Data Analysis | Data Science |
Udacity |
Python Data Analysis | Data Science |
LinkedIn Learning |
Segmentation and Clustering | Data Science |
Udacity |
Python for Data Science Essential Training Part 1 | Data Science |
LinkedIn Learning |
Python for Data Science Essential Training Part 2 | Data Science |
LinkedIn Learning |
Introduction to Machine Learning Course | Machine Learning |
Udacity |
Machine Learning with Scikit-Learn | Machine Learning |
LinkedIn Learning |
Intro to Deep Learning with PyTorch | Deep Learning |
Udacity |
Introduction to Computer Vision | Computer Vision |
Udacity |
OpenCV for Python Developers | Computer Vision |
LinkedIn Learning |
Course | Tags | University |
---|---|---|
Introduction to Computer Vision | Computer Vision |
Brown |
Advances in Computer Vision | Computer Vision |
MIT |
Deep Learning for Computer Vision | Computer Vision Deep Learning |
Stanford |
Course | Year | Instructor | University |
---|---|---|---|
Computer Vision | 2021 | Andreas Geiger | University of Tübingen |
Computer Vision | 2021 | Yogesh S Rawat / Mubarak Shah | University of Central Florida |
Advanced Computer Vision | 2021 | Mubarak Shah | University of Central Florida |
Deep Learning for Computer Vision | 2020 | Justin Johnson | University of Michigan |
Advanced Deep Learning for Computer Vision | 2020 | Laura Leal-Taixé / Matthias Niessner | Technical University of Munich |
Introduction to Digital Image Processing | 2020 | Ahmadreza Baghaie | New York Institute of Technology |
Quantitative Imaging | 2019 | Kevin Mader | ETH Zurich |
Convolutional Neural Networks for Visual Recognition | 2017 | Fei-Fei Li | Stanford University |
Introduction to Digital Image Processing | 2015 | Rich Radke | Rensselaer Polytechnic Institute |
Machine Learning for Robotics and Computer Vision | 2014 | Rudolph Triebel | Technical University of Munich |
Multiple View Geometry | 2013 | Daniel Cremers | Technical University of Munich |
Variational Methods for Computer Vision | 2013 | Daniel Cremers | Technical University of Munich |
Computer Vision | 2012 | Mubarak Shah | University of Central Florida |
Image and video processing | - | Guillermo Sapiro | Duke University |
Library | Description |
---|---|
OpenCV | Open Source Computer Vision Library |
Pillow | The friendly PIL fork (Python Imaging Library) |
scikit-image | collection of algorithms for image processing |
SciPy | open-source software for mathematics, science, and engineering |
mmcv | OpenMMLab foundational library for computer vision research |
imutils | A series of convenience functions to make basic image processing operations |
pgmagick | python based wrapper for GraphicsMagick/ImageMagick |
Mahotas | library of fast computer vision algorithms (last updated: 2021) |
SimpleCV | The Open Source Framework for Machine Vision (last updated: 2015) |
Library | Description |
---|---|
PMT | Piotr's Computer Vision Matlab Toolbox |
matlabfns | MATLAB and Octave Functions for Computer Vision and Image Processing, P. Kovesi, University of Western Australia |
VLFeat | open source library implements popular computer vision algorithms, A. Vedaldi and B. Fulkerson |
MLV | Mid-level Vision Toolbox (MLVToolbox), BWLab, University of Toronto |
ElencoCode | Loris Nanni's CV functions, University of Padova |
Tags: Object Classification [ObjCls]
, Object Detection [ObjDet]
, Object Segmentation [ObjSeg]
, General Library [GenLib]
, Text Reading / Object Character Recognition [OCR]
, Action Recognition [ActRec]
, Object Tracking [ObjTrk]
, Data Augmentation [DatAug]
, Simultaneous Localization and Mapping [SLAM]
, Outlier/Anomaly/Novelty Detection [NvlDet]
, Content-based Image Retrieval [CBIR]
, Image Enhancement [ImgEnh]
, Aesthetic Assessment [AesAss]
, Explainable Artificial Intelligence [XAI]
, Text-to-Image Generation [TexImg]
, Pose Estimation [PosEst]
, Video Matting [VidMat]
, Eye Tracking [EyeTrk]
Repo | Tags | Description |
---|---|---|
computervision-recipes | [GenLib] |
Microsoft, Best Practices, code samples, and documentation for Computer Vision |
FastAI | [GenLib] |
FastAI, Library over PyTorch used for learning and practicing machine learning and deep learning |
pytorch-lightning | [GenLib] |
PyTorchLightning, Lightweight PyTorch wrapper for high-performance AI research |
ignite | [GenLib] |
PyTorch, High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently |
pytorch_geometric | [GenLib] |
Graph Neural Network Library for PyTorch |
kornia | [GenLib] |
Open Source Differentiable Computer Vision Library |
ncnn | [GenLib] |
Tencent, High-performance neural network inference framework optimized for the mobile platform |
MediaPipe | [ObjDet] [ObjSeg] [ObjTrk] [GenLib] |
Google, iOS - Andriod - C++ - Python - Coral, Face Detection - Face Mesh - Iris - Hands - Pose - Holistic - Hair Segmentation - Object Detection - Box Tracking - Instant Motion Tracking - Objectron - KNIFT (Similar to SIFT) |
PyTorch image models | [ObjCls] |
rwightman, PyTorch image classification models, scripts, pretrained weights |
mmclassification | [ObjCls] |
OpenMMLab, Image Classification Toolbox and Benchmark |
vit-pytorch | [ObjCls] |
SOTA for vision transformers |
face_classification | [ObjCls] [ObjDet] |
Real-time face detection and emotion/gender classification |
mmdetection | [ObjDet] |
OpenMMLab, Image Detection Toolbox and Benchmark |
detectron2 | [ObjDet] [ObjSeg] |
Facebook, FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks |
detr | [ObjDet] |
Facebook, End-to-End Object Detection with Transformers |
libfacedetection | [ObjDet] |
An open source library for face detection in images, speed: ~1000FPS |
FaceDetection-DSFD | [ObjDet] |
Tencent, SOTA face detector |
object-Detection-Metrics | [ObjDet] |
Most popular metrics used to evaluate object detection algorithms |
SAHI | [ObjDet] [ObjSeg] |
A lightweight vision library for performing large scale object detection/ instance segmentation |
yolov5 | [ObjDet] |
ultralytics |
AlexeyAB/darknet pjreddie/darknet | [ObjDet] |
YOLOv4 / Scaled-YOLOv4 / YOLOv3 / YOLOv2 |
U-2-Net | [ObjDet] |
ultralytics U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection |
segmentation_models.pytorch | [ObjSeg] |
qubvel, PyTorch segmentation models with pretrained backbones |
mmsegmentation | [ObjSeg] |
OpenMMLab, Semantic Segmentation Toolbox and Benchmark |
mmocr | [OCR] |
OpenMMLab, Text Detection, Recognition and Understanding Toolbox |
pytesseract | [OCR] |
A Python wrapper for Google Tesseract |
EasyOCR | [OCR] |
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc |
PaddleOCR | [OCR] |
Practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices |
PaddleSeg | [ObjSeg] |
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc |
mmtracking | [ObjTrk] |
OpenMMLab, Video Perception Toolbox for object detection and tracking |
mmaction | [ActRec] |
OpenMMLab, An open-source toolbox for action understanding based on PyTorch |
albumentations | [DatAug] |
Fast image augmentation library and an easy-to-use wrapper around other libraries |
ORB_SLAM2 | [SLAM] |
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities |
pyod | [NvlDet] |
Python Toolbox for Scalable Outlier Detection (Anomaly Detection) |
imagededup | [CBIR] |
Image retrieval, CBIR, Find duplicate images made easy! |
image-match | [CBIR] |
Image retrieval, CBIR, Quickly search over billions of images |
Bringing-Old-Photos-Back-to-Life | [ImgEnh] |
Microsoft, Bringing Old Photo Back to Life (CVPR 2020 oral) |
image-quality-assessment | [AesAss] |
Idealo, Image Aesthetic, NIMA model to predict the aesthetic and technical quality of images |
aesthetics | [AesAss] |
Image Aesthetics Toolkit using Fisher Vectors |
pytorch-cnn-visualizations | [XAI] |
Pytorch implementation of convolutional neural network visualization techniques |
DALLE2-pytorch | [TexImg] |
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch |
imagen-pytorch | [TexImg] |
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch |
openpose | [PosEst] |
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation |
RobustVideoMatting | [VidMat] |
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML! |
fastudp | [NvlDet] [CBIR] |
An unsupervised and free tool for image and video dataset analysis |
Random-Erasing | [DatAug] |
Random Erasing Data Augmentation in PyTorch |
CutMix-PyTorch | [DatAug] |
Official Pytorch implementation of CutMix regularizer |
keras-cv | [GenLib] |
Library of modular computer vision oriented Keras components |
PsychoPy | [EyeTrk] |
Library for running psychology and neuroscience experiments |
- PyTorch - CV Datasets, Meta
- Tensorflow - CV Datasets, Google
- CVonline: Image Databases, Edinburgh University, Thanks to Robert Fisher!
- Yet Another Computer Vision Index To Datasets (YACVID), Thanks to Hayko Riemenschneider!
- Kaggle
- PaperWithCode, Meta
- RoboFlow
- VisualData
- CUHK Computer Vision
- VGG - University of Oxford
- MLflow, Platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry
- Apache Airflow, Apache/AirBnB, Platform created by the community to programmatically author, schedule and monitor workflows
- Ploomber, fastest way to build data pipelines.
- VoTT, Microsoft, Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos
- labelme, Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation)
- labelImg, Graphical image annotation tool and label object bounding boxes in images
- VIA, VGG Oxford, HTML-based standalone manual annotation software for image, audio and video
- FiftyOne, open-source tool for building high-quality datasets and computer vision models
- anomaly-detection-resources, Anomaly detection related books, papers, videos, and toolboxes
- awesome-satellite-imagery-datasets List of satellite image training datasets with annotations for computer vision and deep learning
- awesome-Face_Recognition, Computer vision papers about faces.
- the-incredible-pytorch, Curated list of tutorials, papers, projects, communities and more relating to PyTorch
- How to build a good poster - [Link1] [Link2] [Link3]
- How to report a good report - [Link1] [link2]
- The "Python Machine Learning (3rd edition)" book code repository
- Multithreading with OpenCV-Python to improve video processing performance
- Computer Vision Zone - Videos and implementations for computer vision projects
- MadeWithML, Learn how to responsibly deliver value with ML
- d2l-en, Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities
- Writing Pet Peeves, writing guide for correctness, references, and style
- Hitchhiker's Guide to Python, Python best practices guidebook, written for humans
- python-fire, Google, a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
- shotcut, a free, open source, cross-platform video editor.
- PyTorch Computer Vision Cookbook, PyTorch Computer Vision Cookbook, Published by Packt.
- Machine Learning Mastery - Blogs, Blogs written by Jason Brownlee about machine learning.
- PyImageSearch - Blogs, Blogs written by Adrian Rosebrock about computer vision.
- jetson-inference, guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
- CORE Rank A:
- ICCV: International Conference on Computer Vision (IEEE)
- CVPR: Conference on Computer Vision and Pattern Recognition (IEEE)
- ECCV: European Conference on Computer Vision (Springer)
- WACV: Winter Conference/Workshop on Applications of Computer Vision (IEEE)
- ICASSP: International Conference on Acoustics, Speech, and Signal Processing (IEEE)
- MICCAI: Conference on Medical Image Computing and Computer Assisted Intervention (Springer)
- IROS: International Conference on Intelligent Robots and Systems (IEEE)
- ACMMM: ACM International Conference on Multimedia (ACM)
- CORE Rank B
- ACCV: Asian Conference on Computer Vision (Springer)
- VCIP: International Conference on Visual Communications and Image Processing (IEEE)
- ICIP: International Conference on Image Processing (IEEE)
- CAIP: International Conference on Computer Analysis of Images and Patterns (Springer)
- VISAPP: International Conference on Vision Theory and Applications (SCITEPRESS)
- ICPR: International Conference on Pattern Recognition (IEEE)
- ACIVS: Conference on Advanced Concepts for Intelligent Vision Systems (Springer)
- EUSIPCO: European Signal Processing Conference (IEEE)
- ICRA: International Conference on Robotics and Automation (IEEE)
- BMVC: British Machine Vision Conference (organized by BMVA: British Machine Vision Association and Society for Pattern Recognition)
- CORE Rank C:
- ICISP: International Conference on Image and Signal Processing (Springer)
- ICIAR: International Conference on Image Analysis and Recognition (Springer)
- ICVS: International Conference on Computer Vision Systems (Springer)
- Unranked but popular
- MIUA: Conference on Medical Image Understanding and Analysis (organized by BMVA: British Machine Vision Association and Society for Pattern Recognition)
- EUVIP: European Workshop on Visual Information Processing (IEEE, organized by EURASIP: European Association for Signal Processing)
- CIC: Color and Imaging Conference (organized by IS&T: Society for Imaging Science and Technology)
- CVCS: Colour and Visual Computing Symposium
- DSP: International Conference on Digital Signal Processing
- Tier 1
- IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)
- IEEE Transactions on Image Processing (IEEE TIP)
- IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT)
- Springer International Journal of Computer Vision (Springer IJCV)
- Elsevier Pattern Recognition (Elsevier PR)
- Elsevier Computer Vision and Image Understanding (Elsevier CVIU)
- Elsevier Expert Systems with Applications
- Elsevier Neurocomputing, Springer Neural Computing and Applications
- Tier 2
- Elsevier Image and Vision Computing (Elsevier IVC)
- Elsevier Pattern Recognition Letters (Elsevier PR Letters)
- Elsevier Journal of Visual Communication and Image Representation
- Springer Journal of Mathematical Imaging and Vision
- SPIE Journal of Electronic Imaging
- IET Image Processing
- Springer Pattern Analysis and Applications (Springer PAA)
- Springer Machine Vision and Applications (Springer MVA)
- IET Computer Vision
- Open Access
- IEEE Access
- MDPI Journal of Imaging
- International Computer Vision Summer School (IVCSS) [2007-Present], Sicily, Italy [2023]
- Machine Intelligence and Visual Computing Summer School (VISUM) [2013-2022], Porto, Portugal [2022]
- BMVA British Computer Vision Summer School (CVSS) [2013-2020,2023], UK [Website]
-
@AurelienGeron
[Individual]
, Aurélien Géron: former lead of YouTube's video classification team, and author of the O'Reilly book Hands-On Machine Learning with Scikit-Learn and TensorFlow. -
@howardjeremyp
[Individual]
, Jeremy Howard: former president and chief scientist of Kaggle, and co-founder of fast.ai. -
@PieterAbbeel
[Individual]
, Pieter Abbeel: professor of electrical engineering and computer sciences, University of California, Berkeley. -
@pascalpoupart3507
[Individual]
, Pascal Poupart: professor in the David R. Cheriton School of Computer Science at the University of Waterloo. -
@MatthiasNiessner
[Individual]
, Matthias Niessner: Professor at the Technical University of Munich and head of the Visual Computing Lab. -
@MichaelBronsteinGDL
[Individual]
, Michael Bronstein: DeepMind Professor of AI, University of Oxford / Head of Graph Learning Research, Twitter. -
@DeepFindr
[Individual]
, Videos about all kinds of Machine Learning / Data Science topics. -
@deeplizard
[Individual]
, Videos about building collective intelligence. -
@YannicKilcher
[Individual]
, Yannic Kilcher: make videos about machine learning research papers, programming, and issues of the AI community, and the broader impact of AI in society. -
@sentdex
[Individual]
, sentdex: provides Python programming tutorials in machine learning, finance, data analysis, robotics, web development, game development and more. -
@bmvabritishmachinevisionas8529
[Conferences]
, BMVA: British Machine Vision Association. -
@ComputerVisionFoundation
[Conferences]
, Computer Vision Foundation (CVF): co-sponsored conferences on computer vision (e.g. CVPR and ICCV). -
@cvprtum
[University]
, Computer Vision Group at Technical University of Munich. -
@UCFCRCV
[University]
, Center for Research in Computer Vision at University of Central Florida. -
@dynamicvisionandlearninggr1022
[University]
, Dynamic Vision and Learning research group channel! Technical University of Munich. -
@TubingenML
[University]
, Machine Learning groups at the University of Tübingen. -
@computervisiontalks4659
[Talks]
, Computer Vision Talks. -
@freecodecamp
[Talks]
, Videos to learn how to code. -
@LondonMachineLearningMeetup
[Talks]
, Largest machine learning community in Europe. -
@LesHouches-iu6nv
[Talks]
, Summer school on Statistical Physics of Machine learning held in Les Houches, July 4 - 29, 2022. -
@MachineLearningStreetTalk
[Talks]
, top AI podcast on Spotify. -
@WeightsBiases
[Talks]
, Weights and Biases team's conversations with industry experts, and researchers. -
@PreserveKnowledge
[Talks]
, Canada higher education media organization that focuses on advances in mathematics, computer science, and artificial intelligence. -
@TwoMinutePapers
[Papers]
, Two Minute Papers: Explaining AI papers in few mins. -
@TheAIEpiphany
[Papers]
, Aleksa Gordić: x-Google DeepMind, x-Microsoft engineer explaining AI papers. -
@bycloudAI
[Papers]
, bycloud: covers the latest AI tech/research papers for fun. -
Unorganized/Unsorted:
- https://www.youtube.com/@AAmini
- https://www.youtube.com/@WhatsAI
- https://www.youtube.com/@mrdbourke
- https://www.youtube.com/@marksaroufim
- https://www.youtube.com/@NicholasRenotte
- https://www.youtube.com/@abhishekkrthakur
- https://www.youtube.com/@AladdinPersson
- https://www.youtube.com/@CodeEmporium
- https://www.youtube.com/@arp_ai
- https://www.youtube.com/@CodeThisCodeThat
- https://www.youtube.com/@connorshorten6311
- https://www.youtube.com/@SmithaKolan
- https://www.youtube.com/@AICoffeeBreak
- https://www.youtube.com/@independentcode
- https://www.youtube.com/@alfcnz
- https://www.youtube.com/@KapilSachdeva
- https://www.youtube.com/@AICoding
- https://www.youtube.com/@mildlyoverfitted
- Vision Science, announcements about industry/academic jobs in computer vision around the world (in English).
- bull-i3, posts about job opportunities in computer vision in France (in French).