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In our new short course you’ll learn exactly how algorithms like DALL·E and Stable Diffusion work. Dive into the fascinating world of diffusion models and build your own model from scratch with Sharon Zhou ✈️ ICML in "How Diffusion Models Work." Sign up:

DeepLearning.AI

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56,075 次观看 • 3 年前 •via X (Twitter)

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Back in the lab this week updating Kinetic Diffusion, our AI powered dance performance, with new Stable Diffusion models. Speed and pixels have increased tremendously unlocking new opportunities. Here’s an experiment in “popping” new prompts in with connection to the movement ⬇️

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AK

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Excited to share our interview with Sander Dieleman! This is Part 3 in our History of Diffusion series. We talk about diffusion as spectral autoregression, diffusion language models, flow matching, and much more. Enjoy!

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Stability AI

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LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models paper page: github: Recent advancements in text-to-image generation with diffusion models have yielded remarkable results synthesizing highly realistic and diverse images. However, these models still encounter difficulties when generating images from prompts that demand spatial or common sense reasoning. We propose to equip diffusion models with enhanced reasoning capabilities by using off-the-shelf pretrained large language models (LLMs) in a novel two-stage generation process. First, we adapt an LLM to be a text-guided layout generator through in-context learning. When provided with an image prompt, an LLM outputs a scene layout in the form of bounding boxes along with corresponding individual descriptions. Second, we steer a diffusion model with a novel controller to generate images conditioned on the layout. Both stages utilize frozen pretrained models without any LLM or diffusion model parameter optimization. We validate the superiority of our design by demonstrating its ability to outperform the base diffusion model in accurately generating images according to prompts that necessitate both language and spatial reasoning. Additionally, our method naturally allows dialog-based scene specification and is able to handle prompts in a language that is not well-supported by the underlying diffusion model.

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32,888 次观看 • 2 年前

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Slater Stich

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dome | Outlier

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Heng Yang

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We are thrilled to announce "Layered Diffusion Brushes": a real-time training-free image editor powered by diffusion models. 🎨✨ This is new work from my PhD student Peyman Gholami Peyman Gholami. Explore the interactive demo and check out more videos at:

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Y Combinator

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Ethan Mollick

1,769,739 次观看 • 2 年前

How can we train generative models on 100 examples without pretraining on large datasets? Presenting Adaptive IMLE, which outperforms both GANs and diffusion models. Details at Work w/ Mehran Aghabozorgi and Shichong Peng. Come by our #ICML2023 poster Wed AM 1/2

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Ke Li 🍁

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31,490 次观看 • 1 年前