14 datasets found

Groups: Object Detection Formats: JSON

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  • ImageNet2012

    The dataset used in the paper for attention-oriented data analysis and attention-based adversarial defense.

  • PASCAL VOC Dataset

    The PASCAL VOC dataset contains 20 classes, including person, animal, vehicle, and indoor, with 9,963 images containing 24,640 annotated objects.

  • VOC2012

    The VOC2012 dataset is a multi-label image recognition dataset. It contains 11,540 train-val images and 10,991 test images.

  • ImageNet: A Large-Scale Hierarchical Image Database

    The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.

  • PASCAL VOC 2007

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

  • Pascal Visual Object Classes (VOC) Challenge

    The Pascal Visual Object Classes (VOC) challenge is a benchmark for object detection and segmentation.

  • ILSVRC

    ILSVRC is a large-scale image dataset containing over 1.2 million images across 1,000 classes.

  • ImageNet Dataset

    Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in...

  • MS-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...

  • LSUN

    The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

  • 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.

  • 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...

  • ImageNet Large Scale Visual Recognition Challenge

    A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a...

  • 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...