> For the complete documentation index, see [llms.txt](https://paper.lingyunyang.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://paper.lingyunyang.com/paper-list/artificial-intelligence/diffusion-models.md). # Diffusion Models ## Image Generation ### Diffusion Transformer (DiT) * FLUX.1 \[[Code](https://github.com/black-forest-labs/flux)] * Black Forest Labs * Text-to-image generation * Models * FLUX.1-dev: * FLUX.1-schnell: * Scaling Rectified Flow Transformers for High-Resolution Image Synthesis (arXiv:2403.03206) \[[arXiv](https://arxiv.org/abs/2403.03206)] \[[Blog](https://stability.ai/news/stable-diffusion-3)] * Stability AI * **Stable Diffusion 3 (SD3)** * Multimodal Diffusion Transformer (MMDiT) * Models * Stable Diffusion 3 Medium: * Scalable Diffusion Models with Transformers (ICCV 2023) \[[arXiv](https://arxiv.org/abs/2212.09748)] \[[Paper](https://openaccess.thecvf.com/content/ICCV2023/html/Peebles_Scalable_Diffusion_Models_with_Transformers_ICCV_2023_paper.html)] \[[Code](https://github.com/facebookresearch/DiT)] \[[Homepage](https://www.wpeebles.com/DiT)] * UC Berkeley & NYU * **DiT** ### UNet * Kolors: Effective Training of Diffusion Model for Photorealistic Text-to-Image Synthesis \[[Technical Report](https://github.com/Kwai-Kolors/Kolors/blob/master/imgs/Kolors_paper.pdf)] * Kuaishou Kolors * Text-to-image generation * Model: * SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis (arXiv:2307.01952) \[[arXiv](https://arxiv.org/abs/2307.01952)] * Stability AI * Models * * * High-Resolution Image Synthesis with Latent Diffusion Models (CVPR 2022) \[[Paper](https://openaccess.thecvf.com/content/CVPR2022/html/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper)] \[[arXiv](https://arxiv.org/abs/2112.10752)] \[[Code](https://github.com/CompVis/stable-diffusion)] * LMU Munich & Runway ML * Latent Diffusion Models (LDMs) * Models * Stable-Diffusion-v1-5: * Initialized with the weights of the **Stable-Diffusion-v1-2** checkpoint and subsequently fine-tuned on 595k steps at resolution 512x512. ## Video Generation * Stable Video 4D (SV4D) * Stability AI * Model: * Generate **40** frames (5 video frames x 8 camera views) at 576x576 resolution, given 5 reference frames of the same size. * Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets (arXiv:2311.15127) \[[arXiv](https://arxiv.org/abs/2311.15127)] \[[Blog](https://stability.ai/news/stable-video-diffusion-open-ai-video-model)] * Stability AI * **Stable Video Diffusion** (SVD) * Text-to-video and image-to-video generation * Models * * Generate **14** frames at resolution **576x1024** given a context frame of the same size. * * Fine-tuned from the SVD-img2vid. * Generate **25** frames at resolution **576x1024** given a context frame of the same size. ## Acronyms * LLM: Large Language Model --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://paper.lingyunyang.com/paper-list/artificial-intelligence/diffusion-models.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.