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Class Activation Guided Attention Mechanism (CAGAM)

Class Activation Guided Attention Mechanism

2 papers tagged archive 2025-07-28

Introduced by Chinedu Innocent Nwoye et al. in Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

CAGAM is a form of spatial attention mechanism that propagates attention from a known to an unknown context features thereby enhancing the unknown context for relevant pattern discovery. Usually the known context feature is a class activation map (CAM).

PaperSource

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.

Tasks archive 2025-07-28

4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Action Triplet Recognition1
Out of Distribution (OOD) Detection1
Out-of-Distribution Detection1
Triplet1

Usage over time archive 2025-07-28

Papers per year tagged with Class Activation Guided Attention Mechanism: 2021 to 2022, peak 1 1 0 2021: 1 paper 2021 2022: 1 paper 2022
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

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

Attention Mechanisms

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