Difference between revisions of "COCO"
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{{Dataset | {{Dataset | ||
|has full name=Microsoft COCO: Common Objects in Context | |has full name=Microsoft COCO: Common Objects in Context | ||
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|Developed by Institution=Cornell Tech, Toyota Technological Institute, Facebook AI Research, Microsoft Research, Brown University, California Institute of Technology, University of California | |Developed by Institution=Cornell Tech, Toyota Technological Institute, Facebook AI Research, Microsoft Research, Brown University, California Institute of Technology, University of California | ||
| − | |Creation Date=2014 | + | |Developped by (institutions)=Cornell Tech, Toyota Technological Institute, Facebook AI Research, Microsoft Research, Brown University, California Institute of Technology, University of Califorina |
| + | |Creation Date=2014-05-01 | ||
|Dataset Category=Uncontrolled | |Dataset Category=Uncontrolled | ||
|URL=https://cocodataset.org/ | |URL=https://cocodataset.org/ | ||
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|Custodian institution=Microsoft Research, Facebook AI Research, Mighty AI, CVDF | |Custodian institution=Microsoft Research, Facebook AI Research, Mighty AI, CVDF | ||
|has images=330000 | |has images=330000 | ||
|has individuals=250000 | |has individuals=250000 | ||
| + | |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 | ||
| + | |Keywords=Object segmentation, Keypoint, Object Detection | ||
}} | }} | ||
==Description== | ==Description== | ||
Revision as of 16:00, 6 April 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.