Efficient Diffusion Models: A Comprehensive Survey from Principles to
  Practices
As one of the most popular and sought-after generative models in the recent
years, diffusion models have sparked the interests of many researchers and
steadily shown excellent advantage in various generative tasks such as image
synthesis, video generation, molecule design, 3D scene rendering and multimodal
generation, relying on their dense theoretical principles and reliable
application practices. The remarkable success of these recent efforts on
diffusion models comes largely from progressive design principles and efficient
architecture, training, inference, and deployment methodologies. However, there
has not been a comprehensive and in-depth review to summarize these principles
and practices to help the rapid understanding and application of diffusion
models. In this survey, we provide a new efficiency-oriented perspective on
these existing efforts, which mainly focuses on the profound principles and
efficient practices in architecture designs, model training, fast inference and
reliable deployment, to guide further theoretical research, algorithm migration
and model application for new scenarios in a reader-friendly way.
https://github.com/ponyzym/Efficient-DMs-Survey
670f831527d36b2e25ace106
Zhiyuan Ma
670f831527d36b2e25ace107
Yuzhu Zhang
670f831527d36b2e25ace108
Guoli Jia
670f831527d36b2e25ace109
Liangliang Zhao
670f831527d36b2e25ace10a
Yichao Ma
670f831527d36b2e25ace10b
Mingjie Ma
claimed_verified
2024-10-17T11:26:46.424Z
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/avatars/33d3efba541ccc5c9aefe0428d5c20bb.svg
Ma Mingjie
user
MaMJ
670f831527d36b2e25ace10c
Gaofeng Liu
670f831527d36b2e25ace10d
Kaiyan Zhang
claimed_verified
2024-10-16T09:42:56.304Z
60bc94cd85a3ab33829b6211
/avatars/b57d36c7577fbbb42ea5b963eef4144a.svg
Kaiyan Zhang
user
iseesaw
670f831527d36b2e25ace10e
Jianjun Li
670f831527d36b2e25ace10f
Bowen Zhou
Efficient Diffusion Models: A Comprehensive Survey from Principles to
  Practices
As one of the most popular and sought-after generative models in the recent
years, diffusion models have sparked the interests of many researchers and
steadily shown excellent advantage in various generative tasks such as image
synthesis, video generation, molecule design, 3D scene rendering and multimodal
generation, relying on their dense theoretical principles and reliable
application practices. The remarkable success of these recent efforts on
diffusion models comes largely from progressive design principles and efficient
architecture, training, inference, and deployment methodologies. However, there
has not been a comprehensive and in-depth review to summarize these principles
and practices to help the rapid understanding and application of diffusion
models. In this survey, we provide a new efficiency-oriented perspective on
these existing efforts, which mainly focuses on the profound principles and
efficient practices in architecture designs, model training, fast inference and
reliable deployment, to guide further theoretical research, algorithm migration
and model application for new scenarios in a reader-friendly way.
https://github.com/ponyzym/Efficient-DMs-Survey
This survey provides an efficiency-focused overview of diffusion model principles, architecture design, training, inference, and deployment to advance research and application.
diffusion models image synthesis video generation molecule design 3D scene rendering multimodal generation progressive design principles efficient architecture model training fast inference reliable deployment algorithm migration