与baseline Diffusion Models不同的是,Kaleido 引入了一个Autoregressive Model,以T5的decoder进行初始化。Autoregressive Model的目的是将原始的caption条件,离散化成更加丰富的条件。在训练阶段是和Diffusion一起优化的。Text Encoder的输出以cross attention的形式作用在Autoregressive Model上,迭代预测下一个token。最终训练好...
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CVPR2022 | High-Resolution Image Synthesis with Latent Diffusion Models github: https://github.com/CompVis/latent-diffusionmotivation近年来,图像生成领域,扩散概率模型(Diffusion Model, DM)在密度估计和样本质量方面取得了最先进的结果。然而噪音大小和… 真是聪明的...发表于CVPR2... Transformer用于图像复原...
conditional score-based diffusion models 1. 引言 1.1 概述 在当今信息爆炸的时代,如何从海量数据中提取有用的信息已成为一个重要且具有挑战性的问题。随着社交网络和在线平台的迅速发展,人们对于信息扩散过程的理解变得越来越重要。条件分数扩散模型是一种用来建模和预测信息传播的有效工具。它可以帮助我们理解和预测...
Our results are applied to Bessel processes and diffusion models in population genetics. In population genetics, the change of gene frequency is approximated by a one-dimensional diffusion process on [0,1]. We consider the diffusion model with random sampling drift and stochastic selection as the ...
简介:In the world of computer science and machine learning, conditional diffusion models have emerged as a powerful tool for generating diverse and realistic data. However, training these models often requires significant resources and time. In this article, we introduce FreeDoM, a training-free cond...
A Survey on Conditional Image Synthesis with Diffusion Models The repository is based on our recently released survey Conditional Image Synthesis with Diffusion Models: A Survey Zheyuan Zhan, Defang Chen, Jian-Ping Mei, Zhenghe Zhao, Jiawei Chen, Chun Chen, Siwei Lyu, Fellow, IEEE and Can Wang...
Recent research showcases the considerable potential of conditional diffusion models for generating consistent stories. However, current methods, which predominantly generate stories in an autoregressive and excessively caption-dependent manner, often underrate the contextual consistency and relevance of frames ...