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TerraIncognita
The TerraIncognita dataset consists of 24,778 samples from four domains: painting, sketch, cartoon, and photo. -
Towards Unsupervised Domain Generalization
Unsupervised domain generalization (UDG) aims to learn generalizable models with unlabeled data and analyze the effects of pre-training on DG. -
PACS dataset
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... -
PACS, VLCS, Office-Home
The dataset used in the paper for domain generalization tasks. -
Wilds: A Benchmark of In-the-Wild Distribution Shifts
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
Domain generalization for object recognition with multi-task autoencoders. -
Self-Balanced Domain Generalization
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. -
Domain Generalization with MixStyle
The domain generalization with mixstyle dataset -
Deep Domain Generalization (DDG) dataset
The Deep Domain Generalization (DDG) dataset is a dataset for domain generalization. -
Domain Generalization via Jigsaw Puzzle (DGJP) dataset
The Domain Generalization via Jigsaw Puzzle (DGJP) dataset is a dataset for domain generalization using jigsaw puzzle. -
Deeper, Broader and Artier (DBA) dataset
The Deeper, Broader and Artier (DBA) dataset is a large-scale dataset for domain generalization. -
Deeper, broader and artier domain generalization
Deeper, broader and artier domain generalization. -
Cross Domain Generative Augmentation
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...
