Multiscale deformable part model
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
- UC Irvine,University of Chicago,Toyota Technological Institute at Chicago
- Organisation type
- Academia,Academia,Academia
- Country
- United States of America
- Published
- 23 June 2008
- Authors
- Pedro Felzenszwalb, David McAllester, Deva Ramanan
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Object detection
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.
- Record confidence
- Unknown
- Citations
- 3,095
Sources
Where this record came from and when it was last checked.
- Reference
- A discriminatively trained, multiscale, deformable part model
- Last updated
- 1 January 2026
What the numbers mean
Background
Multiscale deformable part model was published by UC Irvine,University of Chicago,Toyota Technological Institute at Chicago, in the country recorded as United States of America, during June 2008. It comes out of an organisation categorised as academia,Academia,Academia.
It works in the domain of Vision, and is recorded as performing the task of object detection.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Multiscale deformable part model — common questions
Multiscale deformable part model— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Multiscale deformable part model— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Multiscale deformable part model— who created it?
It was published by UC Irvine,University of Chicago,Toyota Technological Institute at Chicago, based in United States of America, an organisation categorised as academia,Academia,Academia.
Multiscale deformable part model— when was it released?
It was published in June 2008. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Multiscale deformable part model— what is it used for?
It works in the domain of Vision, and is recorded as handling the task of object detection. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Multiscale deformable part model— what GPU do I need to run it?
None. This 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.