Diffusion Models in Vision: A Survey

Denoising diffusion models represent a recent emerging topic in computer vision, demonstrating remarkable results in the area of generative modeling. Then, we introduce a multi-perspective categorization of diffusion models applied in computer vision.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 A diffusion model is a deep generative model that is based on two stages, a forward diffusion stage and a reverse diffusion stage.
• 2 In the forward diffusion stage, the input data is gradually perturbed over several steps by adding Gaussian noise.
• 3 In the reverse stage, a model is tasked at recovering the original input data by learning to gradually reverse the diffusion process, step by step.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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