Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
json
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
File size: 4,398 Bytes
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---
license: mit
language:
- en
paperswithcode_id: embedding-data/coco_captions
pretty_name: coco_captions
---
# Dataset Card for "coco_captions"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [https://cocodataset.org/#home](https://cocodataset.org/#home)
- **Repository:** [https://github.com/cocodataset/cocodataset.github.io](https://github.com/cocodataset/cocodataset.github.io)
- **Paper:** [More Information Needed](https://arxiv.org/abs/1405.0312)
- **Point of Contact:** [[email protected]]([email protected])
- **Size of downloaded dataset files:**
- **Size of the generated dataset:**
- **Total amount of disk used:** 6.32 MB
### Dataset Summary
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
Disclaimer: The team releasing COCO did not upload the dataset to the Hub and did not write a dataset card.
These steps were done by the Hugging Face team.
### Supported Tasks and Leaderboards
[More Information Needed](https://cocodataset.org/#home)
### Languages
[More Information Needed](https://cocodataset.org/#home)
## Dataset Structure
[More Information Needed](https://cocodataset.org/#format-data)
### Data Instances
[More Information Needed](https://cocodataset.org/#format-data)
### Data Splits
[More Information Needed](https://cocodataset.org/#format-data)
## Dataset Creation
### Curation Rationale
[More Information Needed](https://cocodataset.org/#home)
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed](https://cocodataset.org/#home)
#### Who are the source language producers?
[More Information Needed](https://cocodataset.org/#home)
### Annotations
#### Annotation process
[More Information Needed](https://cocodataset.org/#home)
#### Who are the annotators?
[More Information Needed](https://cocodataset.org/#home)
### Personal and Sensitive Information
[More Information Needed](https://cocodataset.org/#home)
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed](https://cocodataset.org/#home)
### Discussion of Biases
[More Information Needed](https://cocodataset.org/#home)
### Other Known Limitations
[More Information Needed](https://cocodataset.org/#home)
## Additional Information
### Dataset Curators
[More Information Needed](https://cocodataset.org/#home)
### Licensing Information
The annotations in this dataset along with this website belong to the COCO Consortium
and are licensed under a [Creative Commons Attribution 4.0 License](https://creativecommons.org/licenses/by/4.0/legalcode)
### Citation Information
[More Information Needed](https://cocodataset.org/#home)
### Contributions
Thanks to:
- Tsung-Yi Lin - Google Brain
- Genevieve Patterson - MSR, Trash TV
- Matteo R. - Ronchi Caltech
- Yin Cui - Google
- Michael Maire - TTI-Chicago
- Serge Belongie - Cornell Tech
- Lubomir Bourdev - WaveOne, Inc.
- Ross Girshick - FAIR
- James Hays - Georgia Tech
- Pietro Perona - Caltech
- Deva Ramanan - CMU
- Larry Zitnick - FAIR
- Piotr Dollár - FAIR
for adding this dataset.
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