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.
End-to-end learning of compressed video action recognition with decoding-free temporal modeling
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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.