Methods › Computer Vision › Image Model Blocks › Global Local Attention Module
Global Local Attention Module
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The Global Local Attention Module (GLAM) is an image model block that attends to the feature map's channels and spatial dimensions locally, and also attends to the feature map's channels and spatial dimensions globally. The locally attended feature maps, globally attended feature maps, and the original feature maps are then fused through a weighted sum (with learnable weights) to obtain the final feature map.
Paper:
Song, C. H., Han, H. J., & Avrithis, Y. (2022). All the attention you need: Global-local, spatial-channel attention for image retrieval. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 2754-2763).
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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DMAGaze: Gaze Estimation Based on Feature Disentanglement and Multi-Scale Attention 15 Apr 2025 · 0 repositories · arXiv:2504.11160
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All the attention you need: Global-local, spatial-channel attention for image retrieval 16 Jul 2021 · 0 repositories · arXiv:2107.08000
Tasks archive 2025-07-28
8 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| All | 1 |
| Disentanglement | 1 |
| Gaze Estimation | 1 |
| Head Pose Estimation | 1 |
| Image Retrieval | 1 |
| Pose Estimation | 1 |
| Representation Learning | 1 |
| Retrieval | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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