arrow
Return

Tutorial on Diffusion Models for Imaging and Vision

delete2024-01-01
delete0
delete
OA
AI
S
Stanley M. H. Chan *
DOI:10.1561/0600000112delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
The astonishing growth of generative tools in recent years has empowered many exciting applications in text-to-image generation and text-to-video generation. The underlying principle behind these generative tools is the concept of diffusion, a particular sampling mechanism that has overcome some longstanding shortcomings in previous approaches. The goal of this tutorial is to discuss the essential ideas underlying these diffusion models. The target audience of this tutorial includes undergraduate and graduate students who are interested in doing research on diffusion models or applying these tools to solve other problems.

Journal

Foundations and Trends in Computer Graphics and Vision cover
Foundations and Trends in Computer Graphics and Vision
IF:
9.3
Papers:
16
Citations:
458

Organization

Purdue University System cover
Purdue University System
Scholars:
3.9W
Papers: 3.6W
Citations: 66