평범한 필기장

Paper : https://arxiv.org/abs/2212.09748 Scalable Diffusion Models with TransformersWe explore a new class of diffusion models based on the transformer architecture. We train latent diffusion models of images, replacing the commonly-used U-Net backbone with a transformer that operates on latent patches. We analyze the scalability of our Darxiv.orgPaper : https://arxiv.org/abs/2403.03206 Scaling ..

Paper : https://arxiv.org/abs/2406.03293 Text-to-Image Rectified Flow as Plug-and-Play PriorsLarge-scale diffusion models have achieved remarkable performance in generative tasks. Beyond their initial training applications, these models have proven their ability to function as versatile plug-and-play priors. For instance, 2D diffusion models can sarxiv.orgAbstract 본 논문은 기존 diffusion model의 prior..