[Paper] Phased Data Augmentation for Training a Likelihood-Based Generative Model with Limited Data

• Published in: ITE TRANSACTIONS ON MEDIA TECHNOLOGY AND APPLICATIONS Vol. 13; no. 1; pp. 126 - 135
• Main Author: Mimura, Yuta
• Format: Journal Article
• Language: English
• Published: The Institute of Image Information and Television Engineers 2025
• Subjects: data augmentation; generative models; PixelCNNs; training with limited data; VQ-VAE-2

Generative models excel in creating realistic images, yet their dependency on extensive datasets for training presents significant challenges, especially in domains where data collection is costly or challenging. Current data-efficient methods largely focus on Generative Adversarial Network (GAN) ar...