Abstract:Deep learning approaches deliver state-of-the-art performance in recognition of spatiotemporal human motion data. However, one of the main challenges in these recognition tasks is limited available training data. Insufficient training data results in over-fitting and data augmentation is one approach to address this challenge. Existing data augmentation strategies, such as transformations including scaling, shifting and interpolating, require hyperparameter optimization that can easily cost hundreds of GPU hou… Show more
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