Inflated 3D ConvNet
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
- DeepMind,University of Oxford
- Organisation type
- Industry,Academia
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 1 June 2017
- Authors
- Joao Carreira, Andrew Zisserman
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- 3D modeling
- Task
- Action recognition
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
- 240,000 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
- 9,494
Sources
Where this record came from and when it was last checked.
- Reference
- Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
Inflated 3D ConvNet was published by DeepMind,University of Oxford, in the country recorded as United Kingdom of Great Britain and Northern Ireland, during June 2017. It comes out of an organisation categorised as industry,Academia.
It works in the domain of 3D modeling, and is recorded as performing the task of action recognition.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
The training set ran to roughly 240,000 tokens of text.
Its inclusion criterion: highly cited.
Answers
Inflated 3D ConvNet — common questions
Inflated 3D ConvNet— when was it released?
It 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.
Inflated 3D ConvNet— what is it used for?
It works in the domain of 3D modeling, and is recorded as handling the task of action recognition. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Inflated 3D ConvNet— 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.
Inflated 3D ConvNet— 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.
Inflated 3D ConvNet— 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.
Inflated 3D ConvNet— who created it?
It was published by DeepMind,University of Oxford, based in United Kingdom of Great Britain and Northern Ireland, an organisation categorised as industry,Academia.
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.