层级扩散模型(Cascaded Diffusion Model) Imagen利用了一个64x64、256x256、1024x1024等层级分辨率的模型策略。 使用高斯噪声作为数据增强,有助于提升扩散模型的采样质量和超分模型的鲁棒性。 网络结构(Network Architecture) 采用U-Net结构作为64x64文本图像扩散模型的主网络,并进行了一定程度的修改,更名为Efficient U...
The architecture of latent diffusion model. (Image source: Rombach & Blattmann, et al. 2022) 扩散模型的条件生成 (Conditioned Generation) 在使用 ImageNet 数据集等条件信息的图像上训练生成模型时,通常会根据类别标签或一段描述性文本生成样本。 1. 扩散模型的分类器指导(Classifier Guided Diffusion) GLIDE...
The architecture of latent diffusion model. (Image source: Rombach & Blattmann, et al. 2022) 扩散模型的条件生成 (Conditioned Generation) 在使用 ImageNet 数据集等条件信息的图像上训练生成模型时,通常会根据类别标签或一段描述性文本生成样本。 1. 扩散模型的分类器指导(Classifier Guided Diffusion) GLIDE...
Text-to-Image Diffusion Model根据Text Embedding从随机噪声图迭代产生一幅与输入描述匹配的64x64小图,小图由Super-Resolution模块根据Text Embedding放大为256x256的中等尺寸图像,中等尺寸图像由另一个Super-Resolution模块同样根据Text Embedding最终产生1024x1024的高分辨率图像。
by Steven Warren | on 23 DEC 2022 | in Amazon CloudWatch, Amazon EC2, Amazon Elastic Container Service, Architecture | Permalink | Share Stable Diffusion is a state-of-the-art text-to-image model that generates images from text. Deploying text-to-image models such as Stable Diffusion can ...
Text-to-image generation is a type of deep learning task where the goal is to generate realistic images from textual descriptions. The model takes in a textual description as input and produces an image that closely matches the description. Quantization techniques have been used to reduce the ...
256×256 px and 1024×1024 px. The entire model leverages a frozen text encoder derived from the T5 transformer to extract text embeddings. These embeddings are then utilized in a UNet architecture, which is enhanced with cross-attention and attention pooling. As a result, this model surpasses...
1.A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis 介绍了关于GAN生成对抗网络的相关Text-to-Image论文,将其分类为Semantic Enhancement GANs, Resolution Enhancement GANs, Diversity Enhancement GANs, Motion Enhancement GANs四类,介绍了代表性model,如下图所示。
Model Architecture The following figure shows the model architecture: Considering that the complexity of the Transformer model increases quadratically with the length of sequences, the training of the text-to-image generation model is generally carried out in a two-stage combina...
1. A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis 介绍了关于GAN生成对抗网络的相关Text-to-Image论文,将其分类为Semantic Enhancement GANs, Resolution Enhancement GANs, Diversity Enhancement GANs, Motion Enhancement GANs四类,介绍了代表性model,如下图所示。 2. Adversarial...