Multi-task Cascaded CNN
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
- Chinese Academy of Sciences,Chinese University of Hong Kong (CUHK)
- Organisation type
- Academia,Academia
- Country
- China, Hong Kong
- Published
- 26 August 2016
- Authors
- Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, Yu Qiao
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Face 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
- 5,583
Sources
Where this record came from and when it was last checked.
- Reference
- Joint Face Detection and Alignment using Multitask cascaded convolutional networks
- Last updated
- 25 May 2026
What the numbers mean
Background
Multi-task Cascaded CNN was published by Chinese Academy of Sciences,Chinese University of Hong Kong (CUHK), in China, in August 2016. academia,Academia is the category the publisher falls under.
It works in Vision, and is recorded as doing face detection.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
Multi-task Cascaded CNN — common questions
When was Multi-task Cascaded CNN released?
Multi-task Cascaded CNN was published in August 2016. 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 Multi-task Cascaded CNN used for?
Multi-task Cascaded CNN works in Vision, and is recorded as handling face detection. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Multi-task Cascaded CNN?
None. Multi-task Cascaded CNN 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.
Is Multi-task Cascaded CNN open source?
The licensing for Multi-task Cascaded CNN 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 Multi-task Cascaded CNN have?
No parameter count has been published for Multi-task Cascaded CNN, which is why no memory or speed figure appears on this page.
Who created Multi-task Cascaded CNN?
Multi-task Cascaded CNN was published by Chinese Academy of Sciences,Chinese University of Hong Kong (CUHK), based in China, categorised as academia,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.