awesome-visual-attention
github.com/hongyuanyu/awesome-visual-attention ↗A curated list of visual attention modules
11
GitHub Stars
131
Curated Resources
5
Categories
3 hours ago
Last Refreshed
PapersChannel DomainSpatial DomainMix DomainLightweight Transformer Operater
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me efficient vision transformer resources from awesome-visual-attention"
Installation instructions →What's inside
Mix Domain
- AA-Nets
Pytorch Codes
- CBAM
codes/cbam.py
- Split-Attention Networks
Pytorch Codes
Channel Domain
- ECA-Net
codes/ecanet.py
- Effective Squeeze-Excitation
codes/se.py
- FcaNet
codes/fcanet.py
- SKNet
codes/sknet.py
- Squeeze-and-Excitation Networks
codes/senet.py
- Triplet Attention
Pytorch Codes
Spatial Domain
- ISA
Pytorch Codes
- Non-local Neural Networks
Pytorch Codes
- SAGAN
[codes/sa.py]
Showing a sample of 131 resources. View the full list on GitHub →