CvT
ml-cvnets
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| CvT | ml-cvnets | |
|---|---|---|
| 2 | 4 | |
| 515 | 1,681 | |
| 4.1% | 2.9% | |
| 0.0 | 4.8 | |
| 12 months ago | 6 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CvT
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has anyone here implemented Convolutional Vision Transformer (CvT)?
Isn't https://github.com/microsoft/CvT the official code?
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Researchers from McGill University and Microsoft Introduces Convolutional vision Transformer (CvT) that improves Vision Transformer (ViT) in Performance and Efficiency by Introducing Convolutions into ViT
Continue reading | Check out the paper and code.
ml-cvnets
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Apple Researchers Introduce ByteFormer: An AI Model That Consumes Only Bytes And Does Not Explicitly Model The Input Modality - MarkTechPost
https://github.com/apple/ml-cvnets/tree/main/examples/byteformer - Where the code will be located once uploaded
- CVNets - A library for training computer vision networks
- CVNets – A library for training computer vision networks
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Apple ML Researchers Introduce ‘MobileViT’: A Light-Weight And General-Purpose Vision Transformer For Mobile Devices
Github: https://github.com/apple/ml-cvnets
What are some alternatives?
datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
semantic-segmentation-pytorch - Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
convolution-vision-transformers - PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
PaddleViT - :robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
create-go-app - ✨ A complete and self-contained solution for developers of any qualification to create a production-ready project with backend (Go), frontend (JavaScript, TypeScript) and deploy automation (Ansible, Docker) by running only one CLI command.
dytox - Dynamic Token Expansion with Continual Transformers, accepted at CVPR 2022
SINet - Camouflaged Object Detection, CVPR 2020 (Oral)
EfficientFormer - EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
HybridNets - HybridNets: End-to-End Perception Network
Awesome-ComputerVision - Awesome-ComputerVision