40 datasets found

The PST900 dataset is a benchmark for RGB-Thermal semantic segmentation, containing 894 synchronized and calibrated RGB and thermal image pairs with pixel-level human annotations.

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 in high resolution remote sensing images

Semantic segmentation in high resolution remote sensing images

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 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 ADE20K dataset is a large-scale dataset for semantic segmentation. It contains 20,000 images with 150 semantic categories, with 20,000 images for training, 2,000 images for...

Real-time semantic segmentation system for high-resolution images

CamVid dataset is a benchmark dataset for semantic segmentation. It consists of 700 images with 11 object classes.

UAVid is a dataset for semantic segmentation of UAV images, containing 420 images with 8 classes.

The dataset used in the paper is the Pascal VOC 2012 dataset, which is a benchmark for instance segmentation. The dataset consists of 1464 images with 20 class categories and...

COCO Stuff dataset is an extension of the COCO dataset, 164,000 images covering 171 classes are annotated with segmentation masks.

Pyramid scene parsing network for semantic segmentation.

The PASCAL Context dataset is a benchmark for multi-task learning in computer vision. It contains 10103 images with 5 tasks: semantic segmentation, human body part segmentation,...

OneFormer is a universal image segmentation framework jointly trained on the panoptic, semantic, and instance segmentation tasks.

The dataset used in the paper is Pascal Voc 2012 and Cityscapes.