https://github.com/awesomelistsio/awesome-computer-vision
A curated list of awesome libraries, frameworks, tools, datasets, and research papers in computer vision, covering topics such as object detection, image segmentation, 3D vision, and more.
https://github.com/awesomelistsio/awesome-computer-vision
List: awesome-computer-vision
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A curated list of awesome libraries, frameworks, tools, datasets, and research papers in computer vision, covering topics such as object detection, image segmentation, 3D vision, and more.
- Host: GitHub
- URL: https://github.com/awesomelistsio/awesome-computer-vision
- Owner: awesomelistsio
- Created: 2024-11-17T23:36:21.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-11-17T23:37:11.000Z (6 months ago)
- Last Synced: 2025-01-26T22:01:23.574Z (4 months ago)
- Topics: awesome, awesome-list, awesome-lists, computer-vision
- Language: Python
- Homepage: https://www.awesomelists.xyz/
- Size: 4.88 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome-computer-vision - A curated list of awesome libraries, frameworks, tools, datasets, and research papers in computer vision, covering topics such as object detection, image segmentation, 3D vision, and more. (Other Lists / Julia Lists)
README
# Awesome Computer Vision [](https://github.com/awesomelistsio/awesome)
[](https://tinyurl.com/2h9aktmd) [](https://tinyurl.com/d4xnrptz) [](https://tinyurl.com/mr22naua) [](https://tinyurl.com/e8ymxdw3)
> A curated list of awesome libraries, frameworks, tools, datasets, and research papers in computer vision, covering topics such as object detection, image segmentation, 3D vision, and more.
## Contents
- [Libraries and Frameworks](#libraries-and-frameworks)
- [Tools and Applications](#tools-and-applications)
- [Object Detection](#object-detection)
- [Image Segmentation](#image-segmentation)
- [3D Computer Vision](#3d-computer-vision)
- [Face Recognition](#face-recognition)
- [Datasets](#datasets)
- [Research Papers](#research-papers)
- [Learning Resources](#learning-resources)
- [Books](#books)
- [Community](#community)
- [Contribute](#contribute)
- [License](#license)
## Libraries and Frameworks
- [OpenCV](https://opencv.org/) - An open-source library providing computer vision and machine learning algorithms for image and video analysis.
- [Detectron2](https://github.com/facebookresearch/detectron2) - A high-performance object detection library developed by Facebook AI Research.
- [Dlib](http://dlib.net/) - A modern C++ toolkit with machine learning algorithms and tools for computer vision.
- [Scikit-Image](https://scikit-image.org/) - A Python library for image processing, built on top of SciPy.
- [Mediapipe](https://mediapipe.dev/) - A cross-platform framework by Google for building multimodal ML solutions, including face detection and pose estimation.
- [DeepLabV3](https://github.com/tensorflow/models/tree/master/research/deeplab) - A deep learning model for semantic image segmentation.
- [YOLO (You Only Look Once)](https://github.com/AlexeyAB/darknet) - A real-time object detection system.
- [MMDetection](https://github.com/open-mmlab/mmdetection) - An open-source object detection toolbox based on PyTorch.
## Tools and Applications
- [LabelImg](https://github.com/tzutalin/labelImg) - An open-source image annotation tool for labeling datasets.
- [OpenPose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) - A real-time multi-person detection library for human pose estimation.
- [VGG Image Annotator (VIA)](https://www.robots.ox.ac.uk/~vgg/software/via/) - A lightweight tool for manual image annotation.
- [DeepFaceLab](https://github.com/iperov/DeepFaceLab) - A tool for creating deepfakes using face swapping.
- [ImageAI](https://github.com/OlafenwaMoses/ImageAI) - A Python library built to empower developers to build applications using deep learning for computer vision.
## Object Detection
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks (2015)](https://arxiv.org/abs/1506.01497) - The paper introducing Faster R-CNN for object detection.
- [SSD: Single Shot MultiBox Detector (2016)](https://arxiv.org/abs/1512.02325) - A method for real-time object detection.
- [YOLO: You Only Look Once - Unified, Real-Time Object Detection (2016)](https://arxiv.org/abs/1506.02640) - A fast and accurate object detection algorithm.
- [EfficientDet: Scalable and Efficient Object Detection (2020)](https://arxiv.org/abs/1911.09070) - A model architecture focused on balancing accuracy and efficiency.
## Image Segmentation
- [U-Net: Convolutional Networks for Biomedical Image Segmentation (2015)](https://arxiv.org/abs/1505.04597) - A convolutional neural network designed for biomedical image segmentation.
- [DeepLabV3+: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation (2018)](https://arxiv.org/abs/1802.02611) - An advanced model for semantic segmentation.
- [Mask R-CNN (2017)](https://arxiv.org/abs/1703.06870) - An extension of Faster R-CNN for instance segmentation.
- [PSPNet: Pyramid Scene Parsing Network (2017)](https://arxiv.org/abs/1612.01105) - A semantic segmentation model using a pyramid pooling module.
## 3D Computer Vision
- [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017)](https://arxiv.org/abs/1612.00593) - A deep learning model for 3D point cloud processing.
- [NeRF: Neural Radiance Fields for View Synthesis (2020)](https://arxiv.org/abs/2003.08934) - A model for representing 3D scenes using neural networks.
- [Open3D](http://www.open3d.org/) - An open-source library for 3D data processing and visualization.
- [Colmap](https://colmap.github.io/) - A general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline.
## Face Recognition
- [FaceNet: A Unified Embedding for Face Recognition and Clustering (2015)](https://arxiv.org/abs/1503.03832) - A model for face recognition using deep learning.
- [DeepFace: Closing the Gap to Human-Level Performance in Face Verification (2014)](https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf) - A method for facial recognition developed by Facebook.
- [OpenFace](https://cmusatyalab.github.io/openface/) - An open-source deep learning model for face recognition.
- [DeepFaceLab](https://github.com/iperov/DeepFaceLab) - The leading software for creating deepfakes.
## Datasets
- [ImageNet](https://www.image-net.org/) - A large-scale image dataset used for image classification and object detection.
- [COCO (Common Objects in Context)](https://cocodataset.org/) - A dataset for object detection, segmentation, and captioning tasks.
- [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) - A dataset for visual object category recognition and detection.
- [CelebA](https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html) - A large-scale face attributes dataset.
- [KITTI](http://www.cvlibs.net/datasets/kitti/) - A dataset for autonomous driving research.
## Research Papers
- [Visual Attention Mechanisms (2015)](https://arxiv.org/abs/1409.0473) - Introduction of visual attention mechanisms in neural networks.
- [Self-Supervised Learning for Visual Representation (2020)](https://arxiv.org/abs/2006.10029) - A study on self-supervised learning techniques for computer vision tasks.
- [BigGAN: Generative Adversarial Networks for Large-Scale Image Synthesis (2018)](https://arxiv.org/abs/1809.11096) - A generative model for high-quality image synthesis.
## Learning Resources
- [Stanford CS231n: Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu/) - A popular course on computer vision and convolutional networks.
- [Deep Learning for Computer Vision](https://www.coursera.org/specializations/deep-learning) - Part of Andrew Ng’s deep learning specialization on Coursera.
- [PyImageSearch](https://www.pyimagesearch.com/) - A blog and resource hub for computer vision tutorials.
- [Kaggle: Computer Vision Datasets](https://www.kaggle.com/datasets?tags=13212-computer-vision) - A collection of computer vision datasets on Kaggle.
## Books
- *Deep Learning for Computer Vision* by Rajalingappaa Shanmugamani - A guide to deep learning techniques in computer vision.
- *Computer Vision: Algorithms and Applications* by Richard Szeliski - A comprehensive book on computer vision algorithms.
- *Learning OpenCV* by Gary Bradski and Adrian Kaehler - A practical guide to using the OpenCV library.
## Community
- [Reddit: r/ComputerVision](https://www.reddit.com/r/computervision/) - A subreddit for computer vision discussions.
- [PyImageSearch Community](https://www.pyimagesearch.com/community/) - A forum for discussing computer vision and image processing.
- [CVPR Conference](https://cvpr2024.thecvf.com/) - The IEEE Conference on Computer Vision and Pattern Recognition.
- [Kaggle Computer Vision Forum](https://www.kaggle.com/tags/computer-vision/discussion) - A community for computer vision discussions on Kaggle.
## Contribute
Contributions are welcome!
## License
[](http://creativecommons.org/licenses/by-sa/4.0/)