135 datasets found

The SUNRGB-D dataset features 5,285 training and 5,050 test samples from multiple RGB-D cameras. The dataset provides annotations for the first 37 NYUv2 semantic classes and for...

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...

Convolutional Neural Networks (CNNs) have achieved great success due to the powerful feature learning ability of convolution layers. Specifically, the standard convolution...

The Waymo dataset is a LiDAR-based semantic segmentation dataset, which consists of 798 sequences for training and 202 for validation.

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...

Semantic segmentation for medical 3D image stacks enables accurate volumetric reconstructions, computer-aided diagnostics and follow up treatment planning.

Semantic segmentation in high resolution remote sensing images

Semantic segmentation in high resolution remote sensing images

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...

Street View is a large-scale dataset of 3D scenes, consisting of millions of images taken from street-level cameras.

The Foggy Cityscapes dataset is an extension to the Cityscapes dataset, containing 5k diverse real-world urban driving scenes with fog.

The proposed dynamic routing framework for semantic segmentation.

The Argoverse dataset includes 65 training and 24 validation sequences recorded in Miami and Pittsburgh.

The dataset used for one-shot semantic segmentation, including COCO-20i, FSS-1000, and LVIS-92i.

The Gaofen dataset is a high-quality PolSAR semantic segmentation dataset.

The PointNet dataset is used for semantic segmentation of 3D point clouds. It contains annotated point clouds of objects such as table, human, box, robot, and cube.

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.