arxiv Preprint - Conditional Diffusion Distillation

In this episode we discuss Conditional Diffusion Distillation by Kangfu Mei, Mauricio Delbracio, Hossein Talebi, Zhengzhong Tu, Vishal M. Patel, Peyman Milanfar. The authors of this paper propose a new method called conditional distillation to speed up the sampling time of diffusion models in text-to-image generation. The method incorporates image conditions to enhance the diffusion priors and enable conditional sampling with fewer steps. The proposed method simplifies the distillation process by directly distilling the unconditional pre-training in a single stage through joint-learning, and it outperforms existing distillation techniques in terms of sampling time.