CCDM: Continuous Conditional Diffusion Models for Image Generation

arXiv:2405.03546v1 Announce Type: cross
Abstract: Continuous Conditional Generative Modeling (CCGM) aims to estimate the distribution of high-dimensional data, typically images, conditioned on scalar continuous variables known as regression labels. While Continuous conditional Generative Adversarial Networks (CcGANs) were initially designed for this task, their adversarial training mechanism remains vulnerable to extremely sparse or imbalanced data, resulting in suboptimal outcomes. To enhance the quality of generated images, a promising alternative is to replace CcGANs with Conditional Diffusion Models (CDMs), renowned for their …

arxiv continuous cs.cv cs.lg diffusion diffusion models image image generation type