a) Transformer仅用来融合image与text tokens,不直接生成图像,图像生成最终还是使用dVAE的Decoder。 文章中说训练过程dVAE的decoder是fixed,那就说明使用了dVAE。 b) Transformer的Decoder既可以自回归图像,又可以自回归文本(文本本来输入)。 文章说transformer的Loss有两部分,一部分是cross entropy for text,另一部分是...
引用:Ramesh A, Pavlov M, Goh G, et al. Zero-shot text-to-image generation[C]//International conference on machine learning. Pmlr, 2021: 8821-8831. 论文链接:[2102.12092] Zero-Shot Text-to-Image Generation (arxiv.org) 代码链接:https://github.com/openai/DALL-E 简介 传统上,文本到图像生成...
本文也就是DALL·E,用3.3 million image-text pairs训练了一个12B参数的autoregressive transformer,实现了高质量可控的text to image,同时也有zero-shot的能力 project page Method 自回归式的模型处理图片的时候,如果直接把像素拉成序列,当成image token来处理,如果图片分辨率过高,一方面会占用过多的内存,另一方面Likel...
DALL·E有120亿参数,基于自回归transformer,在2.5亿 图片-文本对上训练的。实现了高质量可控的text to image,同时也有zero-shot的能力。 DALL-E没有使用扩散模型,而是dVAE(discrete variational autoencoder离散变分自动编码器)。文中主要和GAN相关模型进行比较,如AttnGAN、DM-GAN、DF-GAM。 1. 介绍 自回归式的模...
Zero-Shot Text-to-Image Generation A. Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, I. Sutskever 2021 CogView: Mastering Text-to-Image Generation via Transformers Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang...
Text-to-image generation has traditionally focused on finding better modeling assumptions for training on a fixed dataset. These assumptions might involve complex architectures, auxiliary losses, or side information such as object part labels or segmentation masks supplied during training. We describe a ...
Image credit: GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion ModelsBenchmarks Add a Result These leaderboards are used to track progress in Zero-Shot Text-to-Image Generation No evaluation results yet. Help compare methods by submitting evaluation metrics. ...
DALL-E: Zero-Shot Text-to-Image Generation Zero-Shot Text-to-Image Generation 论文阅读笔记 摘要: 基于零样本(zero-shot)生成。使用两亿个文本-图像对训练。 公开源码(https://github.com/openai/DALL-E)不是很完善,缺了比如text encoder等关键部分。 这论文写得emmm不堪入目。 效果: 方法 训练阶段分...
Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic - YoadTew/zero-shot-image-to-text
The field of text-to-image generation has witnessed substantial advancements in the preceding years, allowing the generation of high-quality images based solely on text prompts. However, accurately describing objects through text alone is challenging, necessitating the integration of additional modalities ...