13 datasets found

A monocular SLAM system that uses the 2D panoptic segmentation of a sequence of RGB images to create clusters of 3D points according to their class and instance.

The Synthia dataset is a large-scale urban scene understanding dataset, containing 9000 samples. It is used for semantic segmentation tasks.

Depth-aware Video Panoptic Segmentation (DVPS) is a new challenging vision problem that aims to predict panoptic segmentation and depth in a video simultaneously.

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...

The dataset used in the paper is COCO-Panoptic and ADE20K, which are widely used in the field of computer vision.

MaX-DeepLab: End-to-end panoptic segmentation with mask transformers

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.

The COCO test-dev dataset is used for instance segmentation. It contains 20k test-dev images.

The COCO dataset is a large-scale dataset for object detection, semantic segmentation, and captioning. It contains 80 object categories and 1,000 image instances per category,...

Semantic segmentation is one of the fundamental prob-lems in computer vision, whose task is to assign a seman-tic label to each pixel of an image so that different classes can...

The Cityscapes dataset is a large and famous city street scene semantic segmentation dataset. 19 classes of which 30 classes of this dataset are considered for training and...

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...