EDSR
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Seoul National University
- Organisation type
- Academia
- Country
- Korea (Republic of)
- Published
- 10 June 2017
- Authors
- Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, Kyoung Mu Lee
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Image generation
- Task
- Image super-resolution
- Numerical format
- FP32
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Record confidence
- Unknown
- Citations
- 7,151
Sources
Where this record came from and when it was last checked.
- Reference
- Enhanced Deep Residual Networks for Single Image Super-Resolution
- Last updated
- 25 May 2026
What the numbers mean
What this model is
EDSR was published by Seoul National University, in Korea (Republic of), in June 2017. academia is the category the publisher falls under.
It works in Vision, Image generation, and is recorded as doing image super-resolution.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
It is tracked in the underlying dataset for one reason in particular: highly cited.
Answers
EDSR — common questions
Is EDSR open source?
The licensing for EDSR was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does EDSR have?
No parameter count has been published for EDSR, which is why no memory or speed figure appears on this page.
Who created EDSR?
EDSR was published by Seoul National University, based in Korea (Republic of), categorised as academia.
When was EDSR released?
EDSR was published in June 2017. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is EDSR used for?
EDSR works in Vision, Image generation, and is recorded as handling image super-resolution. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run EDSR?
None. EDSR is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.