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Introducing StyleDrop, a model that allows a significantly higher level of stylized text-to-image synthesis by using a few style reference images that describe the style for text-to-image generation, bypassing the burden of text prompt engineering. More→

Google AI

2,426,202 subscribers

80,377 просмотров • 2 лет назад •via X (Twitter)

Искусство Наука и технологии

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Комментарии: 10

Фото профиля kache

kache2 лет назад

model? code?

Фото профиля Alex Volkov (Thursd/AI) 🔜 AIENG summit NY

Alex Volkov (Thursd/AI) 🔜 AIENG summit NY2 лет назад

Shoutout @natanielruizg 👏

Фото профиля Max (e/acc)

Max (e/acc)2 лет назад

Could you please introduce Gemini (at least pro) to EU, and Gemini Ultra to the world?🙂

Фото профиля Digital Adam

Digital Adam2 лет назад

@natanielruizg IPAdapter?

Фото профиля Nader Ale Ebrahim

Nader Ale Ebrahim2 лет назад

Impressive work, @GoogleAI! This innovation promises to simplify the process and enhance the quality of text-to-image generation. Keep pushing the boundaries of AI research! 🌟 #AI #Research #Innovation

Фото профиля takeyourmeds

takeyourmeds2 лет назад

watchumean introducing that's old stuff in stable diffusion like a year old

Фото профиля Rom_AI

Rom_AI2 лет назад

Where is our access, Mr. Google?

Фото профиля Sumone .

Sumone .2 лет назад

Just looking like a wow !!!

Фото профиля Mr.D

Mr.D2 лет назад

That sounds like an exciting advancement in text-to-image synthesis! StyleDrop seems to offer a more efficient approach by utilizing style reference images instead of relying solely on text prompts. This could potentially lead to more accurate and diverse image generation. I'm curious to learn more about how this model works and the results it can produce. @mira_hurley @TimeForPlanX

Фото профиля xiutai

xiutai2 лет назад

@PublicAI_ #AI

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StyleDrop: Text-to-Image Generation in Any Style introduce StyleDrop, a method that enables the synthesis of images that faithfully follow a specific style using a text-to-image model. The proposed method is extremely versatile and captures nuances and details of a user-provided style, such as color schemes, shading, design patterns, and local and global effects. It efficiently learns a new style by fine-tuning very few trainable parameters (less than 1% of total model parameters) and improving the quality via iterative training with either human or automated feedback. Better yet, StyleDrop is able to deliver impressive results even when the user supplies only a single image that specifies the desired style. An extensive study shows that, for the task of style tuning text-to-image models, StyleDrop implemented on Muse convincingly outperforms other methods, including DreamBooth and textual inversion on Imagen or Stable Diffusion. paper page:

StyleDrop: Text-to-Image Generation in Any Style introduce StyleDrop, a method that enables the synthesis of images that faithfully follow a specific style using a text-to-image model. The proposed method is extremely versatile and captures nuances and details of a user-provided style, such as color schemes, shading, design patterns, and local and global effects. It efficiently learns a new style by fine-tuning very few trainable parameters (less than 1% of total model parameters) and improving the quality via iterative training with either human or automated feedback. Better yet, StyleDrop is able to deliver impressive results even when the user supplies only a single image that specifies the desired style. An extensive study shows that, for the task of style tuning text-to-image models, StyleDrop implemented on Muse convincingly outperforms other methods, including DreamBooth and textual inversion on Imagen or Stable Diffusion. paper page:

AK

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Can a small academic team build a strong text-to-image model using only public datasets? Introducing i1: a simple, fully open recipe for strong text-to-image models

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ByteDance announced SeedEdit! A new image model that can edit images with text prompts. It allows for high-resolution editing and supports various changes like local replacements, geometric transformations, and style adjustments. Links ⬇️

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Dreaming Tulpa 🥓👑

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Run InstantStyle Locally with 1 Click InstantStyle lets you generate images with a style of ANY other image, instantly. No LoRA required. Both text-to-image/image-to-image. I wrote a 1 click launcher for the gradio app from Frank (Haofan) Wang (The author of InstantStyle/InstantId!).

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Ideogram AI presents Ideogram 1.0 text-to-image model offers state-of-the-art text rendering, unprecedented photorealism, exceptional prompt adherence, and a new feature called Magic Prompt to help with prompting

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Excited to share a Google DeepMind Gemini 2.0 Flash Image Generation and Editing Quickstart. We build a Next.js reference app on how to use the new image editing feature of Gemini 2.0 Flash. Demo to test ⬇️ > Generate images from text prompts using Gemini 2.0 Flash > Or upload an image and edit it using prompts

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Higgsfield Mod for Minecraft is live. > prompt any building or city, even the Statue of Liberty > create paintings with text-to-image > snap a view and restyle it with image-to-image > make videos from a prompt with text-to-video. > animate in-game photos with image-to-video

Higgsfield Mod for Minecraft is live. > prompt any building or city, even the Statue of Liberty > create paintings with text-to-image > snap a view and restyle it with image-to-image > make videos from a prompt with text-to-video. > animate in-game photos with image-to-video

Higgsfield AI 🧩

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