A volumetric attention(VA) module for 3D medical image segmentation and detection is proposed.

The MSCMRseg dataset consists of images from 45 patients with cardiomyopathy and the gold standard segmentation of LV, MYO and RV.

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

Toward data efficient learning: A benchmark for COVID 19 CT lung and infection segmentation

COVID-19 CT-scans segmentation datasets

The Salinas dataset was acquired over the Salinas Valley in California and gathered by the AVIRIS sensor.

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...

LIDC-IDRI dataset contains almost all the related information for low-dose lung CTs including several doctors' annotations on nodule sizes, locations, diagnosis results, nodule...

ACDC dataset contains 100 samples with the cavity of the right ventricle (RV), the myocardium of the left ventricle (MYO), and the cavity of the left ventricle (LV) to be...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...