61 datasets found

The Animals with Attributes (AwA) dataset consists of 50 classes of animals, with 30,475 images in total.

Visual discrimination puzzles dataset created for few-shot learning problems

Text, tabular and image classification datasets

This dataset is used to evaluate CNNs and human observers on images with a texture-shape cue conflict.

The VIMER-UFO benchmark dataset consists of 8 computer vision tasks: CPLFW, Market1501, DukeMTMC, MSMT-17, Veri-776, VehicleId, VeriWild, and SOP.

A set of binary images of 9 classes, including bird, camel, children, elephant, fork, hammer, key, ray and turtle.

The Imagenet ILSVRC-2012 dataset contains more than 1.2 million training images, 50,000 validation images, and 100,000 test images.

Deep convolutional neural networks have recently proven extremely competitive in challenging image recognition tasks. This paper proposes the epitomic convolution as a new...

The DenseNet dataset is a dataset for image recognition on handwritten digits composed of 60,000 training data and 10,000 test images.

DollarStreet dataset includes 38k images of household objects across homes from 54 countries and with different income levels.

The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category.

A dataset for CAPTCHA recognition

A dataset for CAPTCHA recognition

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

The Office-Home dataset is a visual domain adaptation task, where the goal is to adapt a model trained in a source domain to a target domain with different distributions.

A large-scale fine-grained image recognition dataset containing over 5,000 species of animals and plants.

The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset is a large-scale image classification dataset containing over 14 million images from 21,841 categories.

The dataset used in the paper is the LSUN bedrooms dataset, a large-scale image dataset.

The dataset used for image recognition using deep convolutional neural networks.

The dataset used for image recognition using deep convolutional neural networks.