Attention Mechanisms
Channel & Spatial attention
Introduced by Wang et al. in Residual Attention Network for Image ClassificationChannel & spatial attention combines the advantages of channel attention and spatial attention. It adaptively selects both important objects and regions
Source: Residual Attention Network for Image Classification
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Change Detection | 1 | 16.67% |
| Change detection for remote sensing images | 1 | 16.67% |
| Earth Observation | 1 | 16.67% |
| General Classification | 1 | 16.67% |
| Image Classification | 1 | 16.67% |
| Object Recognition | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
