Object detection is a fundamental task in the field of artificial intelligence, particularly in computer vision. It involves identifying and locating objects within an image or a video frame. This page provides an overview of some popular object detection datasets.

Popular Object Detection Datasets

  • COCO (Common Objects in Context): The COCO dataset is a large-scale dataset for object detection, segmentation, and captioning. It contains over 300,000 images with annotations for 80 object categories, 76 person keypoint annotations, and captions.

    COCO Dataset

  • ImageNet: ImageNet is a large visual database designed for use in visual object recognition software research. It contains over 14 million images, each labeled with at least one object label from a pre-defined set of 21,843 object categories.

    ImageNet Dataset

  • PASCAL VOC (PASCAL Visual Object Classes Challenge): The PASCAL VOC dataset is a popular dataset for object detection and segmentation tasks. It contains over 20,000 images with annotations for 20 object categories.

    PASCAL VOC Dataset

  • Open Images: The Open Images dataset is a large-scale dataset for object detection, scene recognition, and other visual recognition tasks. It contains over 9 million images with annotations for over 600 object categories.

    Open Images Dataset

Further Reading

For more information on object detection datasets and related topics, please visit the following links: