Plug-and-play Module
Plug and play transformer you can find network structure and official complete code by clicking List
The following is to quickly retrieve the core code of the plug-and-play module
CV：
Survey:
| Name | Paper | Time |
|---|---|---|
| Transformers in Vision: A Survey (v1,v2) | Paper:https://arxiv.org/abs/2101.01169 |
2021-01-05
|
| Attention mechanisms and deep learning for machine vision:A survey of the state of the art | Paper:https://arxiv.org/abs/2106.07550 | 2021-06-05 |
| Name | Paper Link | Main idea | Tutorial |
|---|---|---|---|
| 1. Squeeze-and-Excitation | SE | https://github.com/leader402/Plug-and-play/blob/main/cv/tutorial/SE.py | |
| 2. Polarized Self-Attention | PSA | https://github.com/leader402/Plug-and-play/blob/main/cv/tutorial/PSA.py | |
| 3. Dual Attention Network | DaNet | 通道注意力和空间注意力 | https://github.com/leader402/Plug-and-play/blob/main/cv/tutorial/DaNet.py |
| 4. Self-attention | |||
| 5. Masked self-attention | |||
| 6. Multi-head attention | |||
| 7. Attention based deep learning architectures | |||
| 8. Single-channel model | |||
| 9. Multi-channel model | |||
| 10. Skip-layer model | |||
| 11. Bottom-up/top-down model | |||
| 12. CBAM: Convolutional Block Attention Module | CBAM | https://github.com/leader402/Plug-and-play/blob/main/cv/tutorial/CBAM.py |
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19 Nov 05, 2022
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