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COCO - Common Objects in Context

A large-scale object detection, segmentation, and captioning dataset containing images of complex everyday scenes with common objects in their natural context.

About Dataset

COCO is a large-scale computer vision dataset containing images of everyday scenes annotated with object labels, bounding boxes, segmentation masks, and captions. Developed by a consortium of academic and industry researchers, the dataset emphasizes objects in natural contexts rather than isolated images. COCO annotations are rich and fine-grained, supporting multiple vision tasks within a single dataset.

Purpose of Dataset

Coco Is Extensively Used For Benchmarking And Training Computer Vision And Multimodal Models. It Supports Object Detection, Instance Segmentation, Image Captioning, And Visual Question Answering. Researchers Use Coco To Evaluate Model Performance Under Realistic Visual Conditions. For Multimodal Models, Coco Captions And Annotations Help Align Visual Content With Natural Language Descriptions, Improving Cross-modal Understanding.