MS COCO

Description

Introduction:

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.

Website:

https://cocodataset.org

Citation:

Lin T Y, Maire M, Belongie S, et al. Microsoft coco: Common objects in context[C]//Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13. Springer International Publishing, 2014: 740-755.

Including:

Images

• 2014 Train images [83K/13GB]
• 2014 Val images [41K/6GB]
• 2014 Test images [41K/6GB]
• 2015 Test images [81K/12GB]
• 2017 Train images [118K/18GB]
• 2017 Val images [5K/1GB]
• 2017 Test images [41K/6GB]
• 2017 Unlabeled images [123K/19GB]

Annotations

• 2014 Train/Val annotations [241MB]
• 2014 Testing Image info [1MB]
• 2015 Testing Image info [2MB]
• 2017 Train/Val annotations [241MB]
• 2017 Stuff Train/Val annotations [1.1GB]
• 2017 Panoptic Train/Val annotations [821MB]
• 2017 Testing Image info [1MB]
• 2017 Unlabeled Image info [4MB]

Files