Refined Annotations with Soft Labels for Popular Object Detection Datasets
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These datasets contain refined annotations for four popular object detection benchmark datasets:
COCO 2017 validation data, Pascal VOC 2012 detection data for both training and validation split, KITTI 2D object detection training data, and Cityscapes training and validation data. Each annotation consists of a bounding box (xmin, ymin, xmax, ymax) and a soft label annotation ("postprocessed_softlabel") as well as original annotator responses for object categories by annotator ID, including answer times.
Cityscapes Annotations are available through the official Cityscapes platform (https://www.cityscapes-dataset.com/downloads/, "gtBboxValidated_trainval.zip (3.2MB) [md5]")
See the accompanying publication and GitHub repo for more details:
Paper: https://arxiv.org/abs/2609.21822
GitHub: https://github.com/JonathanKlees/Uncertainty-aware-Object-Detection
If you use this dataset, p…
