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Found 3 papers, 2 papers with code
TransformMix: Learning Transformation and Mixing Strategies from Data
Sample-mixing is a popular data augmentation approach that creates additional data by combining existing samples.
AdaAug: Learning Class- and Instance-adaptive Data Augmentation Policies
However, the augmentation policies found are not adaptive to the dataset used, hindering the effectiveness of these AutoDA methods.
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Data augmentation is an efficient way to expand a training dataset by creating additional artificial data.
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