Verified90% confidenceFactTime unknown
Stable Diffusion基于潜在扩散模型(Latent Diffusion Model),通过在压缩的潜在空间中进行去噪过程来生成高质量图像
7
Sources
90%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
awesome-LLM-resources:GitHub 8K Star最全大语言模型学习资源库解析
githubWangRongsheng
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UnverifiedStable Diffusion 基于去噪扩散概率模型(DDPM)理论,将扩散过程从像素空间转移到低维潜在空间,由VAE负责编解码,CLIP模型将文本提示编码为语义向量79% similarUnverifiedDALL·E 2和Stable Diffusion均基于扩散模型原理78% similarUnverified扩散模型(如Stable Diffusion)通过逐步去噪还原图像,擅长细节纹理;自回归多模态模型(如GPT Image 2)在理解复杂文字指令和保持角色一致性方面更具优势77% similarUnverified扩散模型的数学本质是基于随机微分方程和得分匹配理论,支撑着Stable Diffusion、DALL-E等图像生成系统76% similarVerifiedStable Diffusion is built on the Latent Diffusion Model (LDM) architecture76% similar
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