124 datasets found

Pyramid scene parsing network for semantic segmentation.

The bottle, grass, cat, and horse datasets were created for semantic segmentation tasks. The datasets contain images of 4 object types. The ND-MLS dataset was evaluated on...

The ADE-20k dataset, which is a benchmark for semantic understanding of scenes.

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,...

University of Pavia is a popular benchmark dataset for semantic segmentation.

AeroRIT is a large-scale aerial hyperspectral scene with pixel-wise annotations, composed of challenging factors like shadows, glint, and mixed pixels.

Satellite images are an extremely valuable resource in the aftermath of natural disasters such as hurricanes and tsunamis where they can be used for risk assessment and disaster...

The dataset used in the paper is a pre-trained ResNet-50 classifier, which is used for image synthesis, unpaired image-to-image translation, and feature similarity estimation.

A large-scale point cloud classification benchmark, focusing on semantic segmentation of urban scenes.

The Argoverse dataset is a large-scale dataset for autonomous driving, containing 3D point clouds, semantic segmentation masks, and instance segmentation masks.

A dataset of textual entailment tasks, used for evaluating the ability of language models to understand relationships between texts.

The proposed framework for leveraging the semantic segment without transferring any extra bit.

HyperDreamer: Hyper-Realistic 3D Content Generation and Editing from a Single Image

CelebAMask-HQ provides the parsing map of images in CelebA-HQ down-sampled to 512 × 512, where pixel-level annotation of 19 classes, including facial components and accessories,...

The dataset used for the experiments with the proposed approach to augment image data for semantic segmentation networks by applying image-to-image translation with both, a...

A retinal fundus glaucoma challenge dataset.

The BRATS18 multi-modal brain tumor dataset is used for training and testing the proposed TC-MGAN model.

The dataset used in the paper is Argoverse-HD, Cityscapes, and nuScenes.

PASCAL VOC 2007 dataset is a widely used dataset for object detection and semantic segmentation. We use all the split sets (training, validation, testing) in the VOC2007 dataset...

This dataset is used for semantic segmentation of bitewing radiography images. The goal is to segment the images into caries, enamel, dentin, pulp, crowns, restoration and root...