clappoxes2026cc-by-sa-4.0
Off-Road Segmentation Stress Test
165 labeled images of off-road scenes rendered under adverse conditions (dust, night, fog, rain on lens, mud on lens) at three severities each, plus real rain and snow frames, with pixel-level semantic segmentation labels for evaluating perception model robustness.
Downloads26
Episodes165
Why This Matters for Physical AI
This dataset measures how autonomous vehicle perception models degrade under adverse weather and environmental conditions, providing a structured benchmark for identifying domain-shift vulnerabilities critical to deploying robots in real-world off-road scenarios.
Technical Profile
- Modalities
- rgbsemantic_segmentation
- Robot Embodiments
- autonomous_vehicle
- Environment
- outdooroff-road
- Task Types
- semantic_segmentationperception
- Episodes
- 165
- Data Format
- JPEG images with PNG labels
- Annotation Types
- semantic_segmentationpixel-level_labels
- License
- cc-by-sa-4.0
Access
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