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MNIST dataset for handwritten digits
The MNIST dataset is a collection of images of handwritten digits, with size n = 70,000 and D = 784. -
Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
ImageNet2012
The dataset used in the paper for attention-oriented data analysis and attention-based adversarial defense. -
ImageNet Large Scale Visual Recognition Challenge (ILSVRC)
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. -
LSUN Bedrooms
The dataset used in the paper is the LSUN bedrooms dataset, a large-scale image dataset. -
mini-ImageNet
The mini-ImageNet dataset is a subset of the ImageNet dataset, containing 60,000 images from 100 classes. -
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. -
CIFAR10 dataset
The dataset used in this paper is the CIFAR10 dataset, which contains 60,000 32x32 color images in 10 classes, with 6,000 images per class. -
Sprites dataset
The dataset consists of binary images of sprites with variations in the shape (oval, square, and heart) and four geometric factors: scale (6 variation modes), rotation (40), and... -
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. -
Street View House Numbers
The street view house number recognition task involves transcribing an image with house numbers to a string of digits. -
ILSVRC2012
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a subset of the validation dataset used for the ImageNet Large Scale Visual... -
PASCAL VOC 2007
Multi-label image recognition is a practical and challenging task compared to single-label image classification. -
Reading digits in natural images with unsupervised feature learning
The paper presents a method for reading digits in natural images using unsupervised feature learning. -
SVHN Dataset
The dataset used in the paper is a collection of images from the SVHN dataset, along with labels. The dataset is used for image classification.
