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LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference
This is a collection of our NAS and Vision Transformer work.
GhostNet provides a set of efficient AI model architectures and neural network design patterns designed to reduce computation and memory overhead. It serves as a computer vision backbone and a lightweight vision transformer, optimizing the balance between predictive accuracy and inference speed. The project focuses on reducing resource consumption for deployment on mobile devices and edge hardware. It achieves this through the use of lightweight vision transformer implementations and architectures that minimize the total number of parameters. The codebase covers a range of capabilities for i
CVNets: A library for training computer vision networks
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
The main features of leoxiaobin/cvt are: Hybrid Vision Architectures, Vision Backbones and Classification.
Projects with overlapping indexed features include: facebookresearch/levit — LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference. microsoft/cream — This is a collection of our NAS and Vision Transformer work. huawei-noah/ghostnet — GhostNet provides a set of efficient AI model architectures and neural network design patterns designed to reduce… apple/ml-cvnets — CVNets: A library for training computer vision networks. facebookresearch/deit — DeiT is a PyTorch vision transformer framework designed for image classification. It implements a transformer-based… danczs/visformer — This is a pytorch implementation for the Visformer models. This project is based on the training code in DeiT and the…