A UCB-based training procedure switches between a diversity/photorealism score and a feature-cohesion score to select synthetic training images, reporting up to 10-point accuracy gains over static metrics.
International Journal of Computer Vision 127, 302–321 (2019) 20
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Multi-Armed Bandit Approach for Optimizing Training on Synthetic Data
A UCB-based training procedure switches between a diversity/photorealism score and a feature-cohesion score to select synthetic training images, reporting up to 10-point accuracy gains over static metrics.