93 datasets found

The Graphic Narrative Corpus (GNC) is a dataset of annotated comic book pages, representing English-language graphic novels with a variety of styles.

The multimodal brain tumor image segmentation benchmark (brats).

A large-scale computationally annotated dataset of image-mask pairs and a large dataset of unannotated images extracted from video frames.

Panoptic segmentation aims to unify instance and semantic segmentation in the same framework. Existing works propose to merge instance and semantic segmentation using...

Panoptic segmentation aims to unify instance and semantic segmentation in the same framework. Existing works propose to merge instance and semantic segmentation using...

BDD100K Dataset is a large-scale dataset for autonomous driving, containing 100,000 images, with 20,000 images for training and 80,000 images for testing.

Bloodstain pattern analysis dataset for bloodstain image segmentation

Crack detection on UAS-based Imagery using Transfer Learning

The NYU-Depth V2 dataset contains pairs of RGB and depth images collected from Microsoft Kinect in 464 indoor scenes.

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

A dataset of high quality is one of the key factors to train a neural network. Unfortunately, there are few open-source abdominal ultrasound image datasets.

A dataset of high quality is one of the key factors to train a neural network. Unfortunately, there are few open-source abdominal ultrasound image datasets.

CrackSeg9k is a collection of various image datasets showing cracked and uncracked surfaces of multiple building materials.

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics.

SYN70K dataset for smoke segmentation, containing 70k synthetic images.

SMOKE5K dataset for smoke segmentation, containing 400 real images.

SmokeSeg dataset for early smoke segmentation, containing 6144 real images with pixel-wise annotations.

Pyramid scene parsing network for semantic segmentation.

The MNIST(multi) dataset is used to test the ability of TARGET-VAE to identify multiple objects in images.

The dataset used for training and testing the OMG-Seg model, which includes COCO panoptic, COCO-SAM, VIPSeg, Youtube-VIS-2019, and Youtube-VIS-2021 datasets.