Improving Diffusion Models for Class-imbalanced Training Data via Capacity Manipulation

TL;DR

While diffusion models have achieved remarkable performance in image generation, they often struggle with the imbalanced datasets frequently encountered in real-world applications, resulting in significant performance degradation on minority classes. In this paper, we identify model capacity allocation as a key and previously underexplored facto...

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