81 datasets found

Real-world applications of machine learning models often confront data distribution shifts, where discrepancies exist between the training and test data distributions.

A dataset for domain adaptation for LiDAR point cloud semantic segmentation.

A boundary-aware domain adaptation model for LiDAR scan full-scene semantic segmentation (Li-DARNet).

Unsupervised domain adaptation framework for fundus image segmentation

VisDA-C is a dataset for visual domain adaptation, consisting of synthetic rendering of 3D models in the source domain and Microsoft COCO real images in the target domain.

Source-free domain adaptation (SFDA) aims to adapt a source model trained on a fully-labeled source domain to a related but unlabeled target domain.

The paper proposes a Towards Fair Knowledge Transfer (TFKT) framework to handle the fairness challenge in imbalanced cross-domain learning.

The Amazon review dataset is used for multi-source domain adaptation. It contains review texts and ratings of bought products. Products are grouped into categories. Following...

ImageNet-Sketch is used as target dataset for domain adaptation.

SVHN, MNIST, and MNIST-M are used as source datasets for domain adaptation.

Transparent adaptation in deep medical image diagnosis.

Ai-enabled analysis of 3-d ct scans for diagnosis of covid-19 & its severity.

COVID-19 CT Database (COV19-CT-DB) is a dataset used for Covid-19 Detection and Covid-19 Domain Adaptation Challenges.

VisDA-2017 is a simulation-to-real dataset with two extremely distinct domains: Synthetic renderings of 3D models and Real collected from photo-realistic or real-image datasets.

Unsupervised Domain Adaptation (UDA) aims to leverage a label-rich source domain to solve tasks on a related unlabeled target domain.

The GTA5→Cityscapes dataset is a synthetic-to-real benchmark dataset for domain adaptation in semantic segmentation.

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...

This dataset is a continual deepfake detection benchmark, which contains images across different domains.

The Visual Domain Decathlon Benchmark consists of 10 image classification tasks that have been explicitly selected to represent different domains.

The Cityscapes dataset is a large and famous city street scene semantic segmentation dataset. 19 classes of which 30 classes of this dataset are considered for training and...