PRIS-CV/DemoFusion

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2041 stars · 216 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DemoFusion is a CVPR 2024 framework that extends open-source latent diffusion models like SDXL to generate high-resolution images without additional training or paid services. It uses Progressive Upscaling, Skip Residual, and Dilated Sampling to push resolution beyond the model's native limits on consumer hardware.

Use cases

• generate 4k images with stable diffusion
• upscale sdxl output beyond 1024x1024
• high-resolution image generation on low-resource gpu
• democratise high-resolution genai without paywalls
• image-to-image generation at high resolution
• use sdxl with controlnet at high resolution

When to choose

• you need images far above SDXL's native 1024x1024 resolution
• you want to run high-res generation on consumer hardware without paid APIs
• you want progressive previews for rapid prompt iteration
• you want a ComfyUI or HuggingFace-compatible high-res pipeline

When to avoid

• you need fast single-pass generation - DemoFusion requires many progressive passes
• you need to train or fine-tune diffusion models rather than infer with them
• you need non-image modalities like video or audio
• VRAM is extremely limited even for the low-resolution base pass

Facets

library · maturity stable

stable-diffusion image-processing machine-learning llm-inference artificial-intelligence image-processing deep-learning computer-vision python cross-platform high-resolution-generation sdxl diffusion-models progressive-upscaling cvpr-2024 jupyter-notebooks aigc gpu

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