COCO is a large image dataset that is used for object detection and segmentation, key point detection, filling segmentation, and caption generation in the field of machine vision. The dataset focuses on scene understanding, and the objects in the image are accurately segmented for position calibration.

The dataset has three features: target segmentation, scene perception, and superpixel segmentation. It contains 330,000 images, 1.5 million target instances, 80 target classes, 91 item classes, and 250,000 key point characters.

The COCO dataset was released by Microsoft in 2014 and has become a standard testing platform for image captioning.