Fig. 8.

View classification performance of the semi-supervised generative adversarial network for varying amounts of labels as input. The model is able to learn from very small amounts of labeled data (approximately 4% of labels kept with the remaining data as unlabeled) to achieve greater than 80% accuracy for view classification. There exists an exponentially asymptotic behavior over number of labeled samples where accuracy gain becomes less prominent