GFP predicts hierarchical high-level features from a jointly trained lightweight target network instead of reconstructing joint coordinates, speeding up masked skeleton pretraining 6.2x while improving downstream accuracy.
Skeletonmae: Spatial-temporal masked au- toencoders for self-supervised skeleton action recognition
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Towards Efficient General Feature Prediction in Masked Skeleton Modeling
GFP predicts hierarchical high-level features from a jointly trained lightweight target network instead of reconstructing joint coordinates, speeding up masked skeleton pretraining 6.2x while improving downstream accuracy.