59 datasets found

A dataset for unsupervised person re-identification using Generative Adversarial Networks (GANs).

The Birds-to-Words dataset contains 15,931 images (12,770 training and 3,151 testing) tagged with descriptions of fine-grained differences between pairwise bird images.

CIRR is a general image dataset that comprises 36,554 triplets derived from 21,552 images from the popular natural language inference dataset NLVR2.

The FashionIQ dataset contains images of fashion products over 3 categories: Dress, Toptee, and Shirt, with 46,609 images in the training and 31,075 images in the validation set.

Sketchy is a large collection of sketch-photo pairs. The dataset consists of images from 125 different classes, with 100 photos each.

The dataset used in the paper is a multi-view clustering dataset, which contains 6 views of 30000 samples each. The dataset is used to evaluate the performance of the proposed...

The Flickr30k dataset is widely utilized for image caption and image-text retrieval tasks, providing a substantial collection of images with associated captions.

Oxford5k and Paris6k are large-scale image retrieval datasets.

A bipartite interaction graph that contains the edits on Wikipedia pages over a month.

The dataset used in the paper is CUB200-2011, a fine-grained image classification dataset.

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

Fashion Product Images Dataset containing eyewear, footwear, and bags

The DeepFashion dataset is a large-scale dataset for person image synthesis, containing 101,966 pairs of images with different poses and clothing.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used MIT-States, Fashion200k, and COCO 2017 Panoptic Segmentation datasets for...

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 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...

A dataset used for training the image retrieval module

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

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...