Attention Modules
Peer-attention
Introduced by Ryoo et al. in AssembleNet++: Assembling Modality Representations via Attention ConnectionsPeer-attention is a network component which dynamically learns the attention weights using another block or input modality. This is unlike AssembleNet which partially relies on exponential mutations to explore connections. Once the attention weights are found, we can either prune the connections by only leaving the argmax over $h$ or leave them with softmax.
Source: AssembleNet++: Assembling Modality Representations via Attention Connections
Papers
| Paper | Code | Results | Date | Stars |
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Usage Over Time
Components
| Component | Type |
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|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
