Marine surface
ROSEBUD
Fluvial semantic segmentation
549 river images from a USV and canoe in Indiana, with binary water/non-water and seven-class semantic masks at two resolutions.
Access links
Primary places to inspect, download, read about, or reproduce the dataset.
Quick facts
- Vehicle type
- Marine surface
- Environment
- Outdoor
- Data origin
- Real-world
- Sensor count
- 1
- Ground truth
- Not reported
- Calibration
- Not reported
- Annotations
- Available
Sensor overview
High-level sensor availability before the detailed sensor records below.
Ground truth
Reference scope, method, rate, coverage, and provenance.
Not reported
Calibration and synchronization
Reported calibration level, reproducibility signals, and supporting notes.
- Level
- Not reported
- Processed parameters
- Not reported
- Raw calibration data
- Not reported
- Calibration targets
- Not reported
Calibration data
Calibration reproducibility details are not reported.
Notes
Not reportedKnown or intentional limitations
Reported constraints and characteristics to check before using the dataset.
Recorded in summer and fall 2021; winter scenes are proposed as future work.
Small obstacles, little visible water and rapid changes in shadow challenge evaluated networks.
Cameras
river_camera
- Model
- GoPro Hero4
- Setup
- Mono
- Count
- 1
- Effective cameras
- 1
- Modality
- Rgb
- Resolution
- 1920 x 1440
- Rate
- Not reported
- Shutter
- Not Reported
- Lens type
- Not Reported
- HFOV
- Not reported
- VFOV
- Not reported
- Notes
- Released selected images also have 512 x 384 versions. Source video was captured at 30 FPS about 0.5 m above the waterline; 30 FPS is not a released selected-image rate. The paper does not establish the number of distinct physical cameras reused across collection trips.
IMUs
Not reported
GNSS
Not reported
LiDAR
Not reported
Radar
Not reported
Pitot tube
Not reported
Additional sensors
Not reported
Annotations
Reported annotation availability and task support.
- Availability
- Available
- Format
- JPEG images and masks; 8-bit grayscale and RGB masks
- Class count
- 7
Semantic segmentation
Available
Instance segmentation
Not reported
Object detection
Not reported
Optical flow
Not reported
Depth ground truth
Not reported
Citation
Citation key and BibTeX kept at the end of the page for reference.
@article{lambert2022rosebud,
author = {Lambert, Reeve and Chavez-Galaviz, Jalil and Li, Jianwen and Mahmoudian, Nina},
title = {ROSEBUD: A Deep Fluvial Segmentation Dataset for Monocular Vision-Based River Navigation and Obstacle Avoidance},
journal = {Sensors},
year = {2022},
volume = {22},
pages = {4681},
doi = {10.3390/s22134681}
}
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