{"id":20681499,"url":"https://github.com/cizodevahm/learn_computervision","last_synced_at":"2026-03-19T17:03:07.186Z","repository":{"id":255131512,"uuid":"848636169","full_name":"cizodevahm/Learn_ComputerVision","owner":"cizodevahm","description":"A curated list of essential computer vision resources, to kickstart your computer vision learning journey. 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D. Prince 2012\n* [Computer Vision: Theory and Application](http://szeliski.org/Book/) - Rick Szeliski 2010\n* [Computer Vision: A Modern Approach (2nd edition)](http://www.amazon.com/Computer-Vision-Modern-Approach-2nd/dp/013608592X/ref=dp_ob_title_bk) - David Forsyth and Jean Ponce 2011\n* [Learning OpenCV: Computer Vision with the OpenCV Library](http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134) - Gary Bradski and Adrian Kaehler\n* [Neural Networks for Pattern Recognition](http://www.engineering.upm.ro/master-ie/sacpi/mat_did/info068/docum/Neural%20Networks%20for%20Pattern%20Recognition.pdf) - Christopher M. Bishop 1995\n\n## Courses\nOnline courses and tutorials designed to help you learn computer vision, ranging from beginner to expert levels.\n* [Computer Vision: Foundations and Applications](http://vision.stanford.edu/teaching/cs131_fall1415/index.html) - Kalanit Grill-Spector and Fei-Fei Li (Stanford University)\n * [High-Level Vision: Behaviors, Neurons and Computational Models](http://vision.stanford.edu/teaching/cs431_spring1314/) - Fei-Fei Li (Stanford University)\n* [Advances in Computer Vision](http://6.869.csail.mit.edu/fa15/) - Antonio Torralba and Bill Freeman (MIT)\n\n## Papers\nA selection of seminal and recent research papers that have significantly impacted the field of computer vision.\n * [CVPapers](http://www.cvpapers.com/) - Computer vision papers on the web\n * [Computer Vision Foundation open access](http://www.cv-foundation.org/openaccess/menu.py)\n * [Annotated Computer Vision Bibliography](http://iris.usc.edu/Vision-Notes/bibliography/contents.html) - Keith Price (USC)\n\n## Software\nImportant software tools and libraries that are commonly used in computer vision projects, including popular frameworks and packages.\n#### Annotation tools\n* [Comma Coloring](http://commacoloring.herokuapp.com/)\n* [Annotorious](https://annotorious.github.io/)\n* [LabelME](http://labelme.csail.mit.edu/Release3.0/)\n* [gtmaker](https://github.com/sanko-shoko/gtmaker)\n#### Camera calibration\n * [Camera Calibration Toolbox for Matlab](http://www.vision.caltech.edu/bouguetj/calib_doc/)\n * [Camera calibration With OpenCV](http://docs.opencv.org/trunk/doc/tutorials/calib3d/camera_calibration/camera_calibration.html#)\n * [Multiple Camera Calibration Toolbox](https://sites.google.com/site/prclibo/toolbox)\n\n## Datasets\nCurated datasets that are frequently used for training and evaluating computer vision models, including labeled images, videos, and more.\n * [CV Datasets on the web](http://www.cvpapers.com/datasets.html) - CVPapers\n * [Are we there yet?](http://rodrigob.github.io/are_we_there_yet/build/) - Which paper provides the best results on standard dataset X?\n * [Computer Vision Dataset on the web](http://www.cvpapers.com/datasets.html)\n * [Yet Another Computer Vision Index To Datasets](http://riemenschneider.hayko.at/vision/dataset/)\n * [ComputerVisionOnline Datasets](http://www.computervisiononline.com/datasets)\n * [CVOnline Dataset](http://homepages.inf.ed.ac.uk/cgi/rbf/CVONLINE/entries.pl?TAG363)\n * [CV datasets](http://clickdamage.com/sourcecode/cv_datasets.php)\n * [visionbib](http://datasets.visionbib.com/info-index.html)\n * [VisualData](http://www.visualdata.io/)\n * [The KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/eval_stereo_flow.php?benchmark=stero)\n * [LIBELAS: Library for Efficient Large-scale Stereo Matching](http://www.cvlibs.net/software/libelas/)\n * [Ground Truth Stixel Dataset](http://www.6d-vision.com/ground-truth-stixel-dataset)\n\n## Pre-trained Computer Vision Models\n * [List of Computer Vision models](https://github.com/shubham-shahh/Open-Source-Models) These models are trained on custom objects\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcizodevahm%2Flearn_computervision","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcizodevahm%2Flearn_computervision","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcizodevahm%2Flearn_computervision/lists"}