Datasets

RoadAnomaly21

Anomaly track: general anomaly segmentation in full street scenes



RoadObstacle21

Obstacle track: obstacle segmentation with the road as region of interest

Labeling policy

The pixel-level annotations of both datasets include three classes:

The 19 evaluation classes from Cityscapes serve as basis to judge whether an object is anomalous or not. We assign image regions to the void class if they cannot be assigned to any of the Cityscapes classes and also do not belong to the objects / regions of interest, i.e. they are neither anomaly nor obstacle.



Anomaly example

Figure 1: The anomalous object, in this example the caravan, is highlighted in orange and additionally with green contours. The anomalous objects are allowed to appear anywhere in the image.


Obstacle example

Figure 2: The obstacle, in this example a stuffed toy, is highlighted with green contours. The region of interest is given by the road (red contours), darkened regions are excluded from the evaluation.


Download Images

RoadAnomaly21

Mirror 1

uni-wuppertal.sciebo.de

Mirror 2

robotics.ethz.ch

Mirror 3

zenodo.org

RoadObstacle21

Mirror 1

uni-wuppertal.sciebo.de

Mirror 2

robotics.ethz.ch

Mirror 3

zenodo.org