Difference between revisions of "COCO"
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|has full name=Microsoft COCO: Common Objects in Context | |has full name=Microsoft COCO: Common Objects in Context | ||
|Developped by (institutions)=Cornell Tech, Toyota Technological Institute, Facebook AI Research, Microsoft Research, Brown University, California Institute of Technology, University of Califorina | |Developped by (institutions)=Cornell Tech, Toyota Technological Institute, Facebook AI Research, Microsoft Research, Brown University, California Institute of Technology, University of Califorina | ||
| − | | | + | |Developed by (people)=Tsung-Yi Lin, Genevieve Patterson, Matteo R. Ronchi, Yin Cui, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, Larry Zitnick, Piotr Dollár |
|Creation Date=2014-05-01 | |Creation Date=2014-05-01 | ||
|Dataset Category=Uncontrolled | |Dataset Category=Uncontrolled | ||
Revision as of 12:05, 2 May 2022
Technical information:
| Full name | Microsoft COCO: Common Objects in Context |
|---|---|
| Country | |
| Contents | Uncontrolled |
| Images | 330,000 |
| Individuals | 250,000 |
| Runs database software | |
| URL"URL" is a type and predefined property provided by Semantic MediaWiki to represent URI/URL values. | https://cocodataset.org/ |
| Related Technology |
Developers and Users:
Description[edit | ]
COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features:
Object segmentation Recognition in context Superpixel stuff segmentation 330K images (>200K labeled) 1.5 million object instances 80 object categories 91 stuff categories 5 captions per image 250,000 people with keypoints
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This page uses the following references:
- References#_SCITE585a888e59550af899095ce87b01b130
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References
- ^ | Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Bourdev, Lubomir and Girshick, Ross and Hays, James and Perona, Pietro and Ramanan, Deva and Zitnick, C. Lawrence and Dollár, Piotr. Microsoft COCO: Common Objects in Context. , 2015.