including GhostNet, TNT (Transformer in Transformer), AugViT, WaveMLP and ViG developed by Huawei Noah's Ark Lab.
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 | 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 | - |
| ParameterNet | ParameterNet: Parameters Are All You Need. [CVPR 2024]. | ./parameternet_pytorch | - |
@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}
}
This repo provides the TensorFlow/PyTorch code of GhostNet. Other versions and applications can be found in the following: