16 datasets found

The TerraIncognita dataset consists of 24,778 samples from four domains: painting, sketch, cartoon, and photo.

Unsupervised domain generalization (UDG) aims to learn generalizable models with unlabeled data and analyze the effects of pre-training on DG.

The DomainBed dataset is a benchmark for domain generalization, containing five multi-domain datasets (VLCS, PACS, OfficeHome, TerraIncognita, and DomainNet). The dataset is...

The dataset used in the paper is a large collection of small images, each representing a patch of a jigsaw puzzle. The patches are of the same size and orientation, and the goal...

The dataset used in the paper for domain generalization tasks.

The dataset used in the paper is a collection of images for domain generalization tasks, including CIFAR-10-C, CIFAR-100-C, and Digit-DG.

Domain generalization for object recognition with multi-task autoencoders.

Domain generalization aims to learn a prediction model on multi-domain source data such that the model can generalize to a target domain with unknown statistics.

DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control

The domain generalization with mixstyle dataset

The Deep Domain Generalization (DDG) dataset is a dataset for domain generalization.

The Domain Generalization via Jigsaw Puzzle (DGJP) dataset is a dataset for domain generalization using jigsaw puzzle.

The Deeper, Broader and Artier (DBA) dataset is a large-scale dataset for domain generalization.

Deeper, broader and artier domain generalization.

The authors propose a novel data augmentation method called Cross Domain Generative Augmentation (CDGA) to reduce the estimation error of Empirical Risk Minimization (ERM) under...

The dataset used in the paper is a cross-domain dataset, consisting of six domains: Real, Painting, Sketch, Clipart, Infograph, and Quickdraw. Each domain contains 345 object...