81 datasets found

Semantic segmentation is a critical computer vision component of autonomous navigation and robotic systems. It involves dense and high dimensional prediction of a label for...

ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDA

The KiTS19 Challenge Data: a collection of segmented CT imaging and treatment outcomes for 300 patients treated with partial or radical nephrectomy between 2010 and 2018.

A method for LiDAR 3D point-cloud semantic segmentation exploiting perceptual information from RGB images and spatial-depth information from point clouds.

The DeepLab dataset is a benchmark for semantic segmentation.

Few-shot segmentation targets to segment new classes with few annotated images provided. It is more challenging than traditional semantic segmentation tasks that segment known...

Recent work has made significant progress in improving spatial resolution for pixelwise labeling with Fully Convolutional Network (FCN) framework by employing Dilated/Atrous...

Segment Anything in medical images.

Segment Anything (SAM) model for semantic segmentation of medical images.

Semantic segmentation and 3D detection tasks on PartNet and ScanNet datasets

A set of labeled images of printed products at various stages of their production, used for training neural networks for semantic segmentation of manufactured parts and their...

Few-shot segmentation remains challenging due to the limitations of its labeling information for unseen classes. Most previous approaches rely on extracting high-level feature...

The GTA dataset consists of 24966 synthetic images synthetically generated from a video game consisting of outdoor scenes with rich variety of variations in lighting and traffic...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CIFAR-100 and ImageNet-1k datasets for image classification and semantic...

The NYUD-v2 dataset is a benchmark for indoor scene segmentation and depth estimation. It contains 1449 images with 4 tasks: semantic segmentation, depth estimation, surface...

The proposed dynamic routing framework for semantic segmentation.

A dataset of histopathological images for semantic segmentation

The dataset is used for semantic segmentation, and the authors propose a scalable discretization-and-relaxation (SDR) approach to simulate complex scenes.

The dataset used in the paper is a synthetic dataset for image-based object detection tasks, specifically instance segmentation and monocular 3D detection.

SemanticKITTI: A dataset for semantic scene understanding of lidar sequences.