MicroSoft Common Objects in COntext (MS COCO) Dataset
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A MicroSoft Common Objects in COntext (MS COCO) Dataset is an image description dataset that contains image captions that has been made available by Microsoft.
- AKA: MS COCO Dataset.
- Context:
- Available online at: https://cocodataset.org
- Example(s):
- Counter-Example(s):
- See: Reading Comprehension Dataset, COCO Object Detection Task, Joint COCO and LVIS Recognition Challenge Workshop at ECCV 2020, Automatic Image Description Generation Task, ImageNet Large Scale Visual Recognition Challenge (ILSVRC), Image Captions Generation Task, Neural Machine Translation, Natural Language Generation, Training Dataset, Test Dataset, Validation Dataset.
References
2020
- (MS COCO, 2020) ⇒ https://cocodataset.org/#detection-2020 Retrieved:2020-12-12.
- QUOTE: The COCO train, validation, and test sets, containing more than 200,000 images and 80 object categories, are available on the download page. All object instances are annotated with a detailed segmentation mask. Annotations on the training and validation sets (with over 500,000 object instances segmented) are publicly available.
2014
- (Lin et al., 2014) ⇒ Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollar, and C. Lawrence Zitnick. (2014). “Microsoft COCO: Common Objects in Context.” In: Proceeding of the 13th European Conference in Computer Vision Part V (ECCV 2014).
- QUOTE: Objects are labeled using per-instance segmentations to aid in precise object localization. Our dataset contains photos of 91 objects types that would be easily recognizable by a 4 year old. With a total of 2.5 million labeled instances in 328k images, the creation of our dataset drew upon extensive crowd worker involvement via novel user interfaces for category detection, instance spotting and instance segmentation. We present a detailed statistical analysis of the dataset in comparison to PASCAL, ImageNet, and SUN.