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Unsupervised Domain Adaptation using Generative Models and Self-ensembling
The results suggest that selfensembling is better than simple data augmentation with the newly generated data and a single model trained this way can have the best performance across all different transfer tasks.
A Study of Cross-domain Generative Models applied to Cartoon Series
We investigate Generative Adversarial Networks (GANs) to model one particular kind of image: frames from TV cartoons.
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