15 datasets found

Formats: JSON Tags: Image Annotation

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  • OpenImages dataset V6

    The OpenImages dataset V6 contains images with annotations for object detection and instance segmentation tasks.

  • VOC

    The dataset used in the paper is the VOC dataset, which is a dataset for object detection and segmentation.

  • Inria Aerial Image Labeling dataset

    Inria Aerial Image Labeling dataset contains aerial orthorectified color imagery of 5000 × 5000 pixels with a spatial resolution of 0.3 m.

  • AICrowd Mapping Challenge dataset

    AICrowd Mapping Challenge dataset contains 300 × 300 pixels RGB images and corresponding annotations in MS-COCO format.

  • Microsoft COCO: common objects in context

    The COCO dataset is a large-scale dataset for object detection and image classification.

  • Broden

    The dataset used in the paper is Broden, a dataset containing pixel-level concept annotations.

  • PASCAL VOC 2007

    Multi-label image recognition is a practical and challenging task compared to single-label image classification.

  • MSCOCO dataset

    The MSCOCO dataset is a large-scale image captioning dataset, containing 113,287 images with 5,000 validation images and 5,000 test images. The dataset is used for training and...

  • Objects365

    The Objects365 dataset is a large-scale object detection dataset containing 365,000 images with 365 categories.

  • MIR Flickr dataset

    MIR Flickr dataset

  • LabelMe dataset

    The LabelMe dataset is a natural scene dataset used for testing the performance of the IBTM model on image classification tasks.

  • LVIS

    Instance segmentation (IS) is an important computer vision task, aiming at simultaneously predicting the class label and the binary mask for each instance of interest in an image.

  • Cityscapes

    The Cityscapes dataset is a large and famous city street scene semantic segmentation dataset. 19 classes of which 30 classes of this dataset are considered for training and...

  • Microsoft COCO

    The Microsoft COCO dataset was used for training and evaluating the CNNs because it has become a standard benchmark for testing algorithms aimed at scene understanding and...

  • COCO

    Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...
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