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State of the Art on Diffusion Models for Visual Computing
R. Po
, W. Yifan
, V. Golyanik
, K. Aberman
, J. T. Barron
,
A. Bermano
, E. Chan
, T. Dekel
, A. Holynski
, A. Kanazawa
, C. K. Liu
, L. Liu
, B. Mildenhall
, M. Nießner
, B. Ommer
, C. Theobalt
, P. Wonka
, G. Wetzstein
School of Computer Science and AI
Stanford University
Max Planck Institute for Informatics
Snap Inc.
Alphabet Inc.
Weizmann Institute of Science
University of California at Berkeley
University of Pennsylvania
Technical University of Munich
Ludwig Maximilian University of Munich
King Abdullah University of Science and Technology
Research output
:
Contribution to journal
›
Article
›
peer-review
53
Scopus citations
Overview
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Keyphrases
Visual Processing
100%
Diffusion Model
100%
Generative Artificial Intelligence
75%
Diffusion-based
50%
Popular
25%
Locomotion
25%
Personalization
25%
Artificial Intelligence
25%
Rapid Growth
25%
Exponential Growth
25%
ArXiv
25%
Design Decisions
25%
2D Image
25%
Mathematical Concepts
25%
Computer Vision
25%
3D Objects
25%
Image Reconstruction
25%
Computer Graphics
25%
Implementation Details
25%
3D Scene
25%
Keep up
25%
Intelligence Community
25%
Design Implementation
25%
Artificial Intelligence Tools
25%
Implementation Model
25%
Scene Image
25%
Artificial Intelligence Architecture
25%
Stable Diffusion
25%
Vision Intelligence
25%
Video Scene
25%
Computer Science
Diffusion Model
100%
Visual Computing
100%
Generative Artificial Intelligence
75%
Social Implication
25%
Computer Graphic
25%
Starting Point
25%
Implementation Detail
25%
3d Scenes
25%
Exponential Growth
25%
3d video
25%
Intelligence Community
25%
Mathematical Concept
25%
Artificial Intelligence
25%
Computer Vision
25%