including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab.
News
2021/09/28 The paper of TNT (Transformer in Transformer) is accepted by NeurIPS 2021.
2021/09/18 The extended version of Versatile Filters is accepted by T-PAMI.
2021/08/30 GhostNet paper is selected as the Most Influential CVPR 2020 Papers.
2021/08/26 The codes of LegoNet and Versatile Filters has been merged into this repo.
2021/06/15 The code of TNT (Transformer in Transformer) has been released in this repo.
2020/10/31 GhostNet+TinyNet achieves better performance. See details in our NeurIPS 2020 paper: arXiv.
2020/06/10 GhostNet is included in PyTorch Hub.
This repo provides GhostNet pretrained models and inference code for TensorFlow and PyTorch:
- Tensorflow: ./ghostnet_tensorflow with pretrained model.
- PyTorch: ./ghostnet_pytorch with pretrained model.
- We also opensource code on MindSpore Hub and MindSpore Model Zoo.
For training, please refer to tinynet or timm.
This repo provides TinyNet pretrained models and inference code for PyTorch:
- PyTorch: ./tinynet_pytorch with pretrained model.
- We also opensource training code on MindSpore Model Zoo.
This repo provides training code and pretrained models of TNT (Transformer in Transformer) for PyTorch:
- PyTorch: ./tnt_pytorch.
- We also opensource code on MindSpore Model Zoo.
This repo provides the implementation of paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters (ICML 2019)
- PyTorch: ./legonet_pytorch.
This repo provides the implementation of paper Learning Versatile Filters for Efficient Convolutional Neural Networks (NeurIPS 2018)
- PyTorch: ./versatile_filters.
@inproceedings{ghostnet,
title={GhostNet: More Features from Cheap Operations},
author={Han, Kai and Wang, Yunhe and Tian, Qi and Guo, Jianyuan and Xu, Chunjing and Xu, Chang},
booktitle={CVPR},
year={2020}
}
@inproceedings{tinynet,
title={Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets},
author={Han, Kai and Wang, Yunhe and Zhang, Qiulin and Zhang, Wei and Xu, Chunjing and Zhang, Tong},
booktitle={NeurIPS},
year={2020}
}
@inproceedings{tnt,
title={Transformer in transformer},
author={Han, Kai and Xiao, An and Wu, Enhua and Guo, Jianyuan and Xu, Chunjing and Wang, Yunhe},
booktitle={NeurIPS},
year={2021}
}
@inproceedings{legonet,
title={LegoNet: Efficient Convolutional Neural Networks with Lego Filters},
author={Yang, Zhaohui and Wang, Yunhe and Liu, Chuanjian and Chen, Hanting and Xu, Chunjing and Shi, Boxin and Xu, Chao and Xu, Chang},
booktitle={ICML},
year={2019}
}
@inproceedings{wang2018learning,
title={Learning versatile filters for efficient convolutional neural networks},
author={Wang, Yunhe and Xu, Chang and Chunjing, XU and Xu, Chao and Tao, Dacheng},
booktitle={NeurIPS},
year={2018}
}
This repo provides the TensorFlow/PyTorch code of GhostNet. Other versions and applications can be found in the following: