8 datasets found

The dataset used in the paper is SUN Attribute, which consists of 717 classes of images with annotations.

Places205 is a dataset of 2.5 million images from 205 categories, with 12,000 images per category.

The dataset used in the paper is a collection of images of objects with varying viewpoints, used for training and testing the proposed RRB framework.

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

The dataset used in the paper is Places, a large dataset of 400k pairs of images from the Places 205 dataset and corresponding spoken audio captions.

The dataset used in the paper is YFCC100M, a large-scale video dataset. The dataset is used for foreground and background patch extraction and object recognition tasks.

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

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...