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  • GitHub - lllyasviel ControlNet: Let us control diffusion models
    ControlNet is a neural network structure to control diffusion models by adding extra conditions It copys the weights of neural network blocks into a "locked" copy and a "trainable" copy
  • 深入浅出完整解析ControlNet核心基础知识 - 知乎
    在讲解核心原理前,我们先来了解一下在AIGC图像生成 AI绘画生态中,ControlNet是如何使用的。 让大家有一个通俗易懂的直观认识与感受。
  • ControlNet: A Complete Guide - Stable Diffusion Art
    ControlNet is a neural network that controls image generation in Stable Diffusion by adding extra conditions Details can be found in the article Adding Conditional Control to Text-to-Image Diffusion Models by Lvmin Zhang and coworkers
  • lllyasviel ControlNet · Hugging Face
    The ControlNet+SD1 5 model to control SD using human scribbles The model is trained with boundary edges with very strong data augmentation to simulate boundary lines similar to that drawn by human
  • ControlNet:Adding Conditional Control to Text-to-Image . . . - 博客园
    ControlNet 是一种针对文本到图像扩散模型(如 Stable Diffusion)的增强技术,核心目标是借助引入额外的条件输入(如边缘图、姿态图、深度图等),解决传统扩散模型生成结果“不可控”的挑战,让用户能精确引导图像生成的结构、姿态或细节。它由斯坦福大学团队于 2023 年提出,凭借高效
  • Adding Conditional Control to Text-to-Image Diffusion Models
    We present ControlNet, a neural network architecture to add spatial conditioning controls to large, pretrained text-to-image diffusion models
  • ControlNet - Control Diffusion Models | Stable Diffusion Online
    ControlNet is a neural network structure to control diffusion models by adding extra conditions, a game changer for AI Image generation It brings unprecedented levels of control to Stable Diffusion
  • ControlNet 算法原理与代码解释 – Robot 9
    ControlNet 采用了一种类似微调的方法,如下图,在原模型的基础上,增加一个可训练副本,可训练副本的输入是原输入x加上条件c,然后把两个模型的输出相加,可训练副本的输入输出都经过零卷积 (zero convolution)处理,用于在刚开始训练时保持模型的稳定性。




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