recently several interesting implementations have emerged that combine the CLIP model with other generative models to guide the generative latent space search, such as BigSleep and DeepDaze. With the emergence of such open source implementations, the use...
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models 尾巴 背景 在AI应用领域,图像是业界公认最内卷的方向之一,以至于出现很多硕博同学花了几年时光,刚基于当时的SOTA(State Of The Art,业内用于表示“效果最好的方法”),取得了一丢丢微弱的提升,论文都还没写完,某个大佬...
DreamFusion 可以借助预训练 2D text-to-image diffusion model,实现 text-to-3D synthesis。 DreamFusion 引入了一个基于概率分布蒸馏 (probability density distillation) 的 loss,使 2D diffusion model 能够作为参数图像生成器 (parametric image generator) 优化的 prior。 输入文本提示:a DSLR photo of a peacock...
Parti[2]是Google基于多模态AI架构Pathways[10]实现的Text-to-Image模型,其主要模块及工作流程如图2所示,左侧为Transformer Encoder和Transformer Decoder组成的Parti sequence-to-sequence autoregressive model (以下简称text encoder/decoder),右侧为image tokenizer,使用ViT-VQGAN[11]实现,其基础结构也是transformer。 图2...
For text and image generation, the following highlights features in the 2.2 and 2.1 releases that developers can use to enhance their performance on large language and generative AI models: Large Language Model (LLM) optimizations:Intel® Extension for PyTorch* provides optimizations for LLMs in ...
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 combination of image vec...
Discover the top 10 AI image generator apps that seamlessly transform text into stunning visuals. Explore the world of artificial intelligence and unleash your creativity with these cutting-edge tools for text-to-image conversion. Elevate your content wi
In this section, we provide an overview of two popular multimodality models: CLIP (Contrastive Language-Image Pre-training) and BLIP (Bootstrapping Language-Image Pre-training). CLIP model CLIP is a multi-modal vision and language model, which can be u...
Stable Diffusion v2 版本的文本编码器就是用 OpenCLIP 训练的文生图(Text-to-Image)模型。该文本编码器由 LAION 在 Stability AI 的支持下开发,与之前的 V1 版本相比,它极大地提高了生成的图像的质量。此版本中的文生图(Text-to-Image)模型可以生成默认分辨率为 512 x 512 像素和 768 x 768 像素的图像,...
Stable Diffusion v2 版本的文本编码器就是用 OpenCLIP 训练的文生图(Text-to-Image)模型。该文本编码器由 LAION 在 Stability AI 的支持下开发,与之前的 V1 版本相比,它极大地提高了生成的图像的质量。此版本中的文生图(Text-to-Image)模型可以生成默认分辨率为 512 x 512 像素和 768 x 768 像素的图像,...