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Found 2 papers, 1 papers with code
InfoGCN: Representation Learning for Human Skeleton-Based Action Recognition
Human skeleton-based action recognition offers a valuable means to understand the intricacies of human behavior because it can handle the complex relationships between physical constraints and intention.
Ranked #7 on
Skeleton Based Action Recognition
on N-UCLA
The Evolution of Neural Network-Based Chart Patterns: A Preliminary Study
We compared newly found patterns with those found by different search schemes, showing the proposed approach has potential.
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