-
A simple data mixing prior for improving self-supervised learning
A simple data mixing prior for improving self-supervised learning. -
i-mix: A domain-agnostic strategy for contrastive representation learning
A simple framework for contrastive learning of visual representations. -
ciFAIR-100 and ciFAIR-10
ciFAIR-100 and ciFAIR-10 are two datasets created to mimic learning with limited labels. -
Infinite Class Mixup
Mixup is a widely adopted strategy for training deep networks, where additional samples are augmented by interpolating inputs and labels of training pairs. Mixup has shown to... -
TiCC dataset
The TiCC dataset is a dataset of handwritten digits. -
ImageNet Classes
ImageNet classes are used for conditional ImageNet translation. -
PASCAL VOC 2007
Multi-label image recognition is a practical and challenging task compared to single-label image classification. -
Cifar-10 and Cifar-100
The dataset used in the paper is Cifar-10 and Cifar-100, which are commonly used datasets for image classification tasks. -
PicAlert Dataset
This dataset contains Flickr images on various subjects, which are manually labeled as public or private by external viewers. -
Pascal Visual Object Classes (VOC) Challenge
The Pascal Visual Object Classes (VOC) challenge is a benchmark for object detection and segmentation. -
CIFAR-10, CIFAR-100, Tiny ImageNet, SVHN, iSUN, LSUN
CIFAR-10, CIFAR-100, Tiny ImageNet, SVHN, iSUN, LSUN -
Imagenette Dataset
The Imagenette dataset is a zero-shot image classification dataset, containing 13,394 images from ten easily separable classes in ImageNet. -
Counting Digits Dataset
The dataset used in this paper is a synthetic dataset with a nonlinear response, where the response is learned by means of a neural network trained to count numbers in synthetic... -
ImageNet and Super-Resolution Image Datasets
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used ImageNet and several famous super-resolution image datasets.
