diffusion model

[dih-fyoo-zhuhn mod-l]

noun

Computers.

1. a type of machine learning algorithm trained by having the algorithm add noise to images and then remove it from them: used especially for generating pictures from text prompts or for repairing, transforming, or expanding existing images.

Word History and Origins

Origin of diffusion model¹

First recorded in 1995–2000

Example Sentences

At the core of the new system is an advanced generative model known as a diffusion model.

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The technique involves starting with a random 3D representation, rendering a 2D view of a desired object from a random camera angle, adding noise to that image, denoising it with a diffusion model, then optimizing the random 3D representation so it matches the denoised image.

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In the end, they were able to use an off-the-shelf, pretrained image diffusion model to create smooth, realistic-looking 3D shapes without the need for costly retraining.

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Because their method relies on a pretrained diffusion model, it inherits the biases and shortcomings of that model, making it prone to hallucinations and other failures.

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Improving the underlying diffusion model would enhance their process.

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