Attention Mechanisms
Bilinear Attention
Introduced by Fang et al. in Bilinear Attention Networks for Person RetrievalBi-attention employs the attention-in-attention (AiA) mechanism to capture second-order statistical information: the outer point-wise channel attention vectors are computed from the output of the inner channel attention.
Source: Bilinear Attention Networks for Person Retrieval
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Few-Shot Learning | 1 | 16.67% |
| Metric Learning | 1 | 16.67% |
| Machine Reading Comprehension | 1 | 16.67% |
| Question Answering | 1 | 16.67% |
| Text Classification | 1 | 16.67% |
| Person Retrieval | 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 |
