Tsinghua-Daimler Cyclist Detection Benchmark

by X. Li,F. Flohr,Y. Yang,H. Xiong,M. Braun,S. Pan,K. Li,D. M. Gavrila.Unknown

Tsinghua-Daimler Cyclist Detection Benchmark

The Tsinghua-Daimler Cyclist Benchmark provides a benchmark dataset for cyclist detection. Bounding Box based labels are provided for the classes: ("pedestrian", "cyclist", "motorcyclist", "tricyclist", "wheelchairuser", "mopedrider"). The dataset consist of 4 subsets: Train Usually used for training, contains 9741 images with annotations only for "cyclist". Only cyclists which are fully visible (occlusion<10%) and higher than 60 pixels have been labeled here. Valid 1019 images to be used for validation of hyper parameters. Annotations for ("pedestrian", "cyclist", "motorcyclist", "tricyclist", "wheelchairuser", "mopedrider"). Only objects higher than 20 pixels have been labeled here. Test 2914 images normally used for testing with annotations for ("pedestrian", "cyclist", "motorcyclist", "tricyclist", "wheelchairuser", "mopedrider"). Only objects higher than 20 pixels have been labeled here. NonVRU 1000 images in which no object of interest ("pedestrian", "cyclist", "motorcyclist", "tricyclist", "wheelchairuser", "mopedrider") is present.

Dataset Attributes

Label SVG
TasksDetection
Label SVG
CategoriesVehicles, Driving, Riding, Road
Label SVG
SensorRGB Camera

Class Labels

pedestriancyclistmotorcyclisttricyclistwheelchairusermopedrider