awesome-computer-vision
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.
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
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Installation instructions →What's inside
Research Papers
- BigGAN: Generative Adversarial Networks for Large-Scale Image Synthesis (2018)
A generative model for high-quality image synthesis.
- Self-Supervised Learning for Visual Representation (2020)
A study on self-supervised learning techniques for computer vision tasks.
- Visual Attention Mechanisms (2015)
Introduction of visual attention mechanisms in neural networks.
Datasets
- CelebA
A large-scale face attributes dataset.
- COCO (Common Objects in Context)
A dataset for object detection, segmentation, and captioning tasks.
- ImageNet
A large-scale image dataset used for image classification and object detection.
- KITTI
A dataset for autonomous driving research.
- PASCAL VOC
A dataset for visual object category recognition and detection.
3D Computer Vision
- Colmap
A general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline.
- NeRF: Neural Radiance Fields for View Synthesis (2020)
A model for representing 3D scenes using neural networks.
- Open3D
An open-source library for 3D data processing and visualization.
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017)
A deep learning model for 3D point cloud processing.
Community
- CVPR Conference
The IEEE Conference on Computer Vision and Pattern Recognition.
- Kaggle Computer Vision Forum
A community for computer vision discussions on Kaggle.
- PyImageSearch Community
A forum for discussing computer vision and image processing.
- Reddit: r/ComputerVision
A subreddit for computer vision discussions.
Face Recognition
- DeepFace: Closing the Gap to Human-Level Performance in Face Verification (2014)
A method for facial recognition developed by Facebook.
- DeepFaceLab
The leading software for creating deepfakes.
- FaceNet: A Unified Embedding for Face Recognition and Clustering (2015)
A model for face recognition using deep learning.
- OpenFace
An open-source deep learning model for face recognition.
Libraries and Frameworks
- DeepLabV3
A deep learning model for semantic image segmentation.
- Detectron2
A high-performance object detection library developed by Facebook AI Research.
- Dlib
A modern C++ toolkit with machine learning algorithms and tools for computer vision.
- Mediapipe
A cross-platform framework by Google for building multimodal ML solutions, including face detection and pose estimation.
- MMDetection
An open-source object detection toolbox based on PyTorch.
- OpenCV
An open-source library providing computer vision and machine learning algorithms for image and video analysis.
Image Segmentation
- DeepLabV3+: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation (2018)
An advanced model for semantic segmentation.
- Mask R-CNN (2017)
An extension of Faster R-CNN for instance segmentation.
- PSPNet: Pyramid Scene Parsing Network (2017)
A semantic segmentation model using a pyramid pooling module.
- U-Net: Convolutional Networks for Biomedical Image Segmentation (2015)
A convolutional neural network designed for biomedical image segmentation.
Learning Resources
- Deep Learning for Computer Vision
Part of Andrew Ng’s deep learning specialization on Coursera.
- Kaggle: Computer Vision Datasets
A collection of computer vision datasets on Kaggle.
- PyImageSearch
A blog and resource hub for computer vision tutorials.
- Stanford CS231n: Convolutional Neural Networks for Visual Recognition
A popular course on computer vision and convolutional networks.
Showing a sample of 46 resources. View the full list on GitHub →