Statements (52)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:dataset
|
| gptkbp:annotationType |
attributes
labels polygons bounding boxes instance masks tracking IDs |
| gptkbp:citation |
Yu, Fisher, et al. 'BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling.' arXiv preprint arXiv:1805.04687 (2018).
|
| gptkbp:contains |
video sequences
100,000 driving videos annotated images domain adaptation labels drivable area labels instance segmentation labels lane marking labels multi-object tracking labels object detection labels semantic segmentation labels |
| gptkbp:createdBy |
gptkb:Berkeley_Artificial_Intelligence_Research_(BAIR)
|
| gptkbp:domain |
autonomous driving
|
| gptkbp:durationPerVideo |
40 seconds
|
| gptkbp:format |
gptkb:DVD
gptkb:JSON images annotations |
| gptkbp:fullName |
Berkeley DeepDrive 100K dataset
|
| https://www.w3.org/2000/01/rdf-schema#label |
BDD100K dataset
|
| gptkbp:license |
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
|
| gptkbp:numberOfRooms |
100,000
|
| gptkbp:numberOfStudents |
10 (object detection)
40 (semantic segmentation) |
| gptkbp:numberOfVideos |
100,000
|
| gptkbp:refreshRate |
30 fps
|
| gptkbp:relatedTo |
gptkb:Cityscapes_dataset
KITTI dataset nuScenes dataset |
| gptkbp:releaseYear |
2018
|
| gptkbp:resolution |
1280x720 pixels
|
| gptkbp:usedFor |
object detection
semantic segmentation computer vision research scene understanding instance segmentation domain adaptation lane detection autonomous vehicle perception drivable area estimation multi-object tracking |
| gptkbp:website |
https://bdd-data.berkeley.edu/
|
| gptkbp:分布地区 |
gptkb:United_States
|
| gptkbp:bfsParent |
gptkb:Berkeley_DeepDrive
|
| gptkbp:bfsLayer |
7
|