Latent-based Diffusion Model for Long-tailed Recognition

arXiv:2404.04517v1 Announce Type: new
Abstract: Long-tailed imbalance distribution is a common issue in practical computer vision applications. Previous works proposed methods to address this problem, which can be categorized into several classes: re-sampling, re-weighting, transfer learning, and feature augmentation. In recent years, diffusion models have shown an impressive generation ability in many sub-problems of deep computer vision. However, its powerful generation has not been explored in long-tailed problems. We propose a new approach, the Latent-based Diffusion Model for Long-tailed Recognition …

abstract applications arxiv augmentation computer computer vision cs.ai cs.cv diffusion diffusion model diffusion models distribution feature issue practical recognition sampling transfer transfer learning type vision