Efficient AI Backbones

including GhostNet, TNT (Transformer in Transformer), AugViT, WaveMLP and ViG developed by Huawei Noah's Ark Lab.

• News
• Model zoo
• Citation
• Other versions

News

2023/02/27 The paper of ParameterNet is accepted by CVPR 2024.

2022/12/01 The code of NeurIPS 2022 (Spotlight) GhostNetV2 is released at ./ghostnetv2_pytorch.

2022/11/13 The code of IJCV 2022 G-Ghost RegNet is released at ./g_ghost_pytorch.

2022/06/17 The code of NeurIPS 2022 Vision GNN (ViG) is released at ./vig_pytorch.

2022/02/06 Transformer in Transformer (TNT) is selected as the Most Influential NeurIPS 2021 Papers.

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.

Model zoo

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}
}
@inproceedings{tang2021augmented,
  title={Augmented shortcuts for vision transformers},
  author={Tang, Yehui and Han, Kai and Xu, Chang and Xiao, An and Deng, Yiping and Xu, Chao and Wang, Yunhe},
  booktitle={NeurIPS},
  year={2021}
}
@inproceedings{tang2022image,
  title={An Image Patch is a Wave: Phase-Aware Vision MLP},
  author={Tang, Yehui and Han, Kai and Guo, Jianyuan and Xu, Chang and Li, Yanxi and Xu, Chao and Wang, Yunhe},
  booktitle={CVPR},
  year={2022}
}
@inproceedings{han2022vig,
  title={Vision GNN: An Image is Worth Graph of Nodes}, 
  author={Kai Han and Yunhe Wang and Jianyuan Guo and Yehui Tang and Enhua Wu},
  booktitle={NeurIPS},
  year={2022}
}
@article{tang2022ghostnetv2,
  title={GhostNetV2: Enhance Cheap Operation with Long-Range Attention},
  author={Tang, Yehui and Han, Kai and Guo, Jianyuan and Xu, Chang and Xu, Chao and Wang, Yunhe},
  journal={arXiv preprint arXiv:2211.12905},
  year={2022}
}

Other versions of GhostNet

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