Plug and play transformer you can find network structure and official complete code by clicking List

Overview

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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Comments
  • 总体进度

    总体进度

    总体进度

    1. Squeeze-and-Excitation:张一极(completed)
    2. Polarized Self-Attention:望之
    3. Dual Attention Network:望之(completed)
    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:望之(completed)
    总体进度 
    opened by AllenZYJ 0
Owner
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