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Found 2 papers, 1 papers with code
From Movements to Metrics: Evaluating Explainable AI Methods in Skeleton-Based Human Activity Recognition
The advancement of deep learning in human activity recognition (HAR) using 3D skeleton data is critical for applications in healthcare, security, sports, and human-computer interaction.
AutoGCN -- Towards Generic Human Activity Recognition with Neural Architecture Search
This paper introduces AutoGCN, a generic Neural Architecture Search (NAS) algorithm for Human Activity Recognition (HAR) using Graph Convolution Networks (GCNs).
Ranked #56 on
Skeleton Based Action Recognition
on NTU RGB+D
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