A Person Independence Universal Micro-action Recognition Framework combines Distributionally Robust Optimization with temporal-frequency alignment at the feature level and group-invariant regularization at the loss level to improve generalization across persons on the MA-52 dataset.
On the convergence of distributionally robust optimization methods
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Every Subtlety Counts: Fine-grained Person Independence Micro-Action Recognition via Distributionally Robust Optimization
A Person Independence Universal Micro-action Recognition Framework combines Distributionally Robust Optimization with temporal-frequency alignment at the feature level and group-invariant regularization at the loss level to improve generalization across persons on the MA-52 dataset.