151 datasets found

The ThinObject dataset is used for evaluation, which consists of 500 samples.

The HRSOD dataset is used for evaluation, which consists of 287 samples.

The COIFT dataset is used for evaluation, which consists of 280 samples.

The DIS-VD dataset is used for evaluation, which consists of 470 samples.

The DIS-5K dataset is used for evaluation, which consists of 3,000 samples for training, 470 for validation, and 2,000 for testing (partitioned into four subsets DIS-TE1∼DIS-TE4).

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.

Document layout analysis (DLA) is crucial for understanding the physical layout and logical structure of documents, serving information retrieval, document summarization,...

The Microsoft Common Objects in Context (COCO) dataset is a benchmark for object detection, segmentation, and image classification.

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

Polyp segmentation using U-Net-ResNet50

Organ at risk (OAR) segmentation is a crucial step for treatment planning and outcome determination in radiotherapy treatments of cancer patients.

The COCO+LVIS dataset contains millions of high-quality labels for natural images.

A public PSV dataset for parking slot and lane markings segmentation

The dataset used in this paper for multi-sensor next-best-view planning as matroid-constrained submodular maximization.

The RIM-ONE-r3 dataset contains 60 test images.

The Refuge challenging data set contains 400 train, 400 validation, and 400 test images.

Convex shapes are common priors for optic disc and cup segmentation in eye fundus images. This method is proposed to guarantee that outputs are convex shapes.

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,...

MRI anonymization dataset