including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab.

• GhostNet Code
• TinyNet Code
• TNT Code
• Citation
• Other versions

News

2021/06/15 The code of TNT (Transformer in Transformer) has been released in this repo.

2020/11/10 The code of TinyNet (NeurIPS 2020) has been release at MindSpore Model Zoo.

2020/10/31 GhostNet+TinyNet achieves better performance. See details in our NeurIPS 2020 paper: arXiv.

2020/09/24 We release GhostNet models for more vision tasks on MindSpore Hub and MindSpore Model Zoo.

2020/06/10 GhostNet is included in PyTorch Hub.

This repo provides 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 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 of TNT (Transformer in Transformer) for PyTorch:

• PyTorch: ./tnt_pytorch.
• We also opensource code on MindSpore Model Zoo.

@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}
}
@article{tnt,
  title={Transformer in transformer},
  author={Han, Kai and Xiao, An and Wu, Enhua and Guo, Jianyuan and Xu, Chunjing and Wang, Yunhe},
  journal={arXiv preprint arXiv:2103.00112},
  year={2021}
}

This repo provides the TensorFlow/PyTorch code of GhostNet. Other versions and applications can be found in the following:

0. timm: code with pretrained model
1. Darknet: cfg file, and description
2. Gluon/Keras/Chainer: code
3. Paddle: code
4. Bolt inference framework: benckmark
5. Human pose estimation: code
6. YOLO with GhostNet backbone: code
7. Face recognition: cavaface, FaceX-Zoo, TFace