Automotive
SynthmanticLiDAR
LiDAR semantic segmentation and synthetic-to-real transfer
CARLA-generated semantic LiDAR dataset with 48,000 scans in eight sequences, designed for transfer to SemanticKITTI.
Access links
Primary places to inspect, download, read about, or reproduce the dataset.
Quick facts
- Vehicle type
- Automotive
- Environment
- Outdoor
- Data origin
- Simulation
- 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.
Eight sequences contain 6,000 scans each across seven CARLA maps. The 16,000-scan LT subset uses the first 2,000 scans of each sequence and overlaps the full collection.
The release is synthetic; simulator geometry and class distributions do not remove the domain gap to physical LiDAR.
SemanticKITTI classes other-vehicle, other-ground, parking and trunk are absent from the shared evaluation labels.
RGB examples in the paper do not establish a released camera stream. Trajectory references, scan frequency and calibration packaging are not established.
Cameras
Not reported
IMUs
Not reported
GNSS
Not reported
LiDAR
CARLA simulated LiDAR
- Model or name
- CARLA simulated LiDAR
- Count
- 1
- Dimensions
- 3
- Rate
- Not reported
- Channels
- 64
- Range
- 80 m
Radar
Not reported
Additional sensors
Not reported
Annotations
Reported annotation availability and task support.
- Availability
- Available
- Format
- Per-point simulator semantic labels: 30 classes, with 15 shared SemanticKITTI evaluation classes.
- Class count
- 30
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.
@inproceedings{montalvo2024synthmanticlidar,
author = {Montalvo, Javier and Carballeira, Pablo and García-Martín, Álvaro},
title = {{SynthmanticLiDAR}: A Synthetic Dataset for Semantic Segmentation on {LiDAR} Imaging},
booktitle = {2024 IEEE International Conference on Image Processing (ICIP)},
year = {2024},
pages = {137--143},
doi = {10.1109/ICIP51287.2024.10648055}
}Dataset corrections
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