All Projects → huawei-noah → Ghostnet

huawei-noah / Ghostnet

Licence: apache-2.0
CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.

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CV Backbones

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.


GhostNet Code

This repo provides GhostNet pretrained models and inference code for TensorFlow and PyTorch:

For training, please refer to tinynet or timm.

TinyNet Code

This repo provides TinyNet pretrained models and inference code for PyTorch:

TNT Code

This repo provides training code and pretrained models of TNT (Transformer in Transformer) for PyTorch:

LegoNet Code

This repo provides the implementation of paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters (ICML 2019)

Versatile Filters Code

This repo provides the implementation of paper Learning Versatile Filters for Efficient Convolutional Neural Networks (NeurIPS 2018)

Citation

@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}
}

Other versions of GhostNet

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

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