Ghostnet Save

Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

Project README

Efficient AI Backbones

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

News

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.

2021/09/28 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.

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

Model zoo

Model Paper Pytorch code MindSpore code
GhostNet GhostNet: More Features from Cheap Operations. [CVPR 2020] ./ghostnet_pytorch MindSpore Model Zoo
GhostNetV2 GhostNetV2: Enhance Cheap Operation with Long-Range Attention. [NeurIPS 2022 Spotlight] ./ghostnetv2_pytorch MindSpore Model Zoo
G-GhostNet GhostNets on Heterogeneous Devices via Cheap Operations. [IJCV 2022] ./g_ghost_pytorch MindSpore Model Zoo
TinyNet Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets. [NeurIPS 2020] ./tinynet_pytorch MindSpore Model Zoo
TNT Transformer in Transformer. [NeurIPS 2021] ./tnt_pytorch MindSpore Model Zoo
PyramidTNT PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture. [CVPR 2022 Workshop] ./tnt_pytorch MindSpore Model Zoo
CMT CMT: Convolutional Neural Networks Meet Vision Transformers. [CVPR 2022] ./cmt_pytorch MindSpore Model Zoo
AugViT Augmented Shortcuts for Vision Transformers. [NeurIPS 2021] ./augvit_pytorch MindSpore Model Zoo
SNN-MLP Brain-inspired Multilayer Perceptron with Spiking Neurons. [CVPR 2022] ./snnmlp_pytorch MindSpore Model Zoo
WaveMLP An Image Patch is a Wave: Quantum Inspired Vision MLP. [CVPR 2022] ./wavemlp_pytorch MindSpore Model Zoo
ViG Vision GNN: An Image is Worth Graph of Nodes. [NeurIPS 2022] ./vig_pytorch -
LegoNet LegoNet: Efficient Convolutional Neural Networks with Lego Filters. [ICML 2019] ./legonet_pytorch -
Versatile Filters Learning Versatile Filters for Efficient Convolutional Neural Networks. [NeurIPS 2018] ./versatile_filters -

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:

  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
Open Source Agenda is not affiliated with "Ghostnet" Project. README Source: huawei-noah/Efficient-AI-Backbones

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