Two-stream ConvNets for action recognition
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
- University of Oxford
- Organisation type
- Academia
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 9 June 2014
- Authors
- Karen Simonyan, Andrew Zisserman
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Video
- Task
- Video classification
- 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
- 1,289,500 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
- 8,181
Sources
Where this record came from and when it was last checked.
- Reference
- Two-Stream Convolutional Networks for Action Recognition in Videos
- Last updated
- 25 May 2026
What the numbers mean
Background
Two-stream ConvNets for action recognition was published by University of Oxford, in the country recorded as United Kingdom of Great Britain and Northern Ireland, during June 2014. It comes out of an organisation categorised as academia.
It works in the domain of Video, and is recorded as performing the task of video classification.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
What went into building it
It was trained on a corpus of about 1,289,500 tokens of text.
Its inclusion criterion: highly cited.
Answers
Two-stream ConvNets for action recognition — common questions
Two-stream ConvNets for action recognition— who created it?
It was published by University of Oxford, based in United Kingdom of Great Britain and Northern Ireland, an organisation categorised as academia.
Two-stream ConvNets for action recognition— when was it released?
It was published in June 2014. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Two-stream ConvNets for action recognition— what is it used for?
It works in the domain of Video, and is recorded as handling the task of video classification. These are the areas it was designed around; they describe intent rather than a hard boundary.
Two-stream ConvNets for action recognition— 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.
Two-stream ConvNets for action recognition— 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.
Two-stream ConvNets for action recognition— 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.
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.