Diffusion Models in Vision: A Survey
University of Bucharest · University of Central Florida
Abstract
Denoising diffusion models represent a recent emerging topic in computer vision, demonstrating remarkable results in the area of generative modeling. A diffusion model is a deep generative model that is based on two stages, a forward diffusion stage and a reverse diffusion stage. In the forward diffusion stage, the input data is gradually perturbed over several steps by adding Gaussian noise. 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. Diffusion models are widely appreciated for the quality and diversity of the generated samples, despite their known computational burdens, i.e., low speeds due to the high…
Citation impact
- FWCI
- 178.32
- Percentile
- 100%
- References
- 259
Authors
4Topics & keywords
- Computer science
- Artificial intelligence
- Diffusion
- Diffusion process
- Machine learning
- Noise (video)
- Noise reduction
- Algorithm