Statements (57)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Data
|
| gptkbp:analysis |
visualization tools available
|
| gptkbp:annotation_tools |
Label Me, VGG Image Annotator
|
| gptkbp:application |
computer vision, machine learning
|
| gptkbp:available_formats |
images, annotations
|
| gptkbp:benchmark_competitions |
CVPR, ECCV
|
| gptkbp:categories |
road, vehicles, pedestrians
|
| gptkbp:class |
gptkb:30
|
| gptkbp:collaborator |
various universities and research institutions
|
| gptkbp:collection |
driving through cities
|
| gptkbp:contains |
street scenes
|
| gptkbp:contribution |
open-source projects
|
| gptkbp:created_by |
gptkb:Max_Planck_Institute_for_Informatics
|
| gptkbp:data_annotation |
manual and semi-automated
|
| gptkbp:data_challenges_addressed |
real-world application of AI
|
| gptkbp:data_ethics |
considerations for data use
|
| gptkbp:data_labeling |
multi-class labeling
|
| gptkbp:data_preprocessing |
normalization, augmentation
|
| gptkbp:data_size |
over 25 GB
|
| gptkbp:data_type |
JPEG images
benchmark dataset supports various ML frameworks |
| gptkbp:dataset_citations |
cited in numerous papers
|
| gptkbp:dataset_collaborations |
partnerships with tech companies
|
| gptkbp:dataset_features |
high-resolution images
|
| gptkbp:dataset_goals |
improve scene understanding
|
| gptkbp:dataset_impact |
advancing urban scene understanding
|
| gptkbp:dataset_limitations |
limited to urban scenes
|
| gptkbp:dataset_popularity |
widely used in research
|
| gptkbp:dataset_updates |
periodic updates
|
| gptkbp:evaluates |
mean Intersection over Union (m Io U)
|
| gptkbp:focus |
urban environments
|
| gptkbp:focus_area |
German cities
|
| gptkbp:has_artwork |
5000
|
| https://www.w3.org/2000/01/rdf-schema#label |
Cityscapes dataset
|
| gptkbp:image |
camera footage
|
| gptkbp:image_diversity |
various weather conditions
|
| gptkbp:is_divided_into |
train, val, test
|
| gptkbp:is_documented_in |
gptkb:JSON
pixel-level annotations |
| gptkbp:license |
gptkb:Creative_Commons_Attribution_4.0_International_License
|
| gptkbp:primary_use |
autonomous driving research
|
| gptkbp:product_quality |
high-quality annotations
|
| gptkbp:provides_information_on |
encourages collaboration
free for research purposes image segmentation challenges |
| gptkbp:related_datasets |
gptkb:ADE20_K
|
| gptkbp:release_year |
gptkb:2016
|
| gptkbp:resolution |
2048x1024
|
| gptkbp:training_models |
Deep Lab, FCN
|
| gptkbp:trends |
growing interest in urban datasets
|
| gptkbp:used_for |
semantic segmentation
|
| gptkbp:user_base |
researchers, developers, students
|
| gptkbp:website |
https://www.cityscapes-dataset.com
|
| gptkbp:bfsParent |
gptkb:Mask_R-CNN
gptkb:Seg_Net |
| gptkbp:bfsLayer |
5
|