75 datasets found

Groups: Image Classification Formats: JSON

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  • MobileNet

    MobileNet is a compact network working accurately and efficiently based on light-weight module of separable convolution layers.

  • Pascal VOC

    Semantic segmentation is a crucial and challenging task for image understanding. It aims to predict a dense labeling map for the input image, which assigns each pixel a unique...

  • CIFAR10 and CIFAR100

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors conducted experiments on various vision tasks, including image classification,...

  • 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...

  • CUB-200

    CUB-200 is a fine-grained image classification dataset containing high resolution images of 200 different bird species.

  • DomainNet

    The dataset used in the paper is a cross-domain dataset, consisting of six domains: Real, Painting, Sketch, Clipart, Infograph, and Quickdraw. Each domain contains 345 object...

  • ImageNet-10 Dataset

    The ImageNet-10 dataset is a subset of the ImageNet-1K dataset, containing images from 10 classes.

  • 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.

  • CIFAR-10, CIFAR-100, and ImageNet

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, and ImageNet datasets.

  • 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...

  • Learning Multiple Layers of Features from Tiny Images

    The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.

  • CIFAR-10 and ImageNet

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CLIP model and the CIFAR-10 and ImageNet datasets.

  • 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...