将图像tokens和嵌入的文本tokens concat起来并通过T5X的Transformer自注意力编码器进行编码。关键词对齐头使用修改后的文本提示作为目标,通过T5X解码器解码连接后图像文本特征向量预测出对齐不良的关键词。 感觉整体结构还是比较简单的,文中作者也提出了另一种变体:既然我们要预测七个目标(图中蓝色字体),能不能直接搞一...
定制化文生图目前在学术界的定义,有多个表示,例如Personalized Text-to-Image Generation,image customization, subject-driven image generation/editing。广义上来说,针对给定的图片概念,作为目标生成图片的前景,围绕该前景物体做任何生成以及编辑操作,都可以算作定制化文生图。具体对任务定义感兴趣可以参考 (牛力:三线交汇...
Do I need to be a tech-savvy person in order to use AI? Are images created by the AI image generator copyrighted? How much does the AI image generator cost? Why do I get different images when using the same prompt? How do I write good prompts?
Discover the magic of AI image generation. When used as an AI picture generator, Adobe Express powered by Firefly makes creative exploration easier and faster for everyone. Use Generate image to experiment with your wildest ideas, find new sources of inspiration, or create eye-catching content in...
has been upgraded again. It integrates with advanced text-to-image generation architectures, Transformer and VQGAN. At the same time, it gives free access to the open-source community for the checkpoints of Chinese text-to-image generation models with different parameters an...
Controllable Text-to-Image Generation 论文阅读笔记 github代码地址:https://github.com/mrlibw/ControlGAN 关键词:T2I,文本生成图像,ControlGAN Introduction: 现在的许多模型如果改变了输入文本的其中一个部分,那么输出的图片会与原来文本生成的图片大相径庭,没法实现一部分的修改。如下图所示。
Rich Human Feedback for Text-to-Image Generation(UCSD & Google 2024) 182播放 Mip-Splatting Alias-free 3D Gaussian Splatting(Tubingen 2024) 253播放 7月6日组会:2024CVPR 中使用3DGS的SLAM 517播放 减论:5分钟极减阅读CVPR24 best paper《Generative Image Dynamics》 1.0万播放 港科大最新!Vista:高保真...
CLICK for the full abstract Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge of interest in the delicate refinement of text prompts. Users assign weights or alter the...
可以看出,总损失的第一项LG,原理与StackGAN中的无条件+有条件结构相似,无条件损失确定图像是真实的还是假的,条件损失确定图像和句子是否相符。 没看StackGAN++可以点击->:Text to image论文精读 StackGAN++ 而损失函数的第二项LDAMSM是由DAMSM计算的字符级细粒度图像-文本匹配损失,这部分在本博文的第七节中介绍。
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