Tsinghua-Daimler Cyclist Detection Benchmark
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This page covers the Tsinghua-Daimler Cyclist Detection Benchmark Dataset introduced in

X. Li, F. Flohr, Y. Yang, H. Xiong, M. Braun, S. Pan, K. Li and D. M. Gavrila. A New Benchmark for Vision-Based Cyclist Detection. In Proc. of the IEEE Intelligent Vehicles Symposium (IV), Gothenburg, Sweden, pp.1028-1033, 2016.

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 Statistics

Training

Validation

Test

Non-VRU

Total

# image frames

9741

1019

2914

1000

14674

# cyclist BBs

16202

1314

4657

0

22173

# pedestrian BBs

0 (ignored)

1541

7401

0

8942

# other rider BBs

0 (ignored)

190

1105

0

1295

# total BBs

16202

3045

13163

0

32410

Example videos

License Terms

This dataset is made freely available non-commercial purposes such as academic research, teaching, scientific publications, or personal experimentation. Permission is granted to use, copy, and distribute the data given that you agree:

  1. That the dataset comes "AS IS", without express or implied warranty. Although every effort has been made to ensure accuracy, Daimler (or the website host) does not accept any responsibility for errors or omissions.
  2. That you include a reference to the above publication in any published work that makes use of the dataset.
  3. That if you have altered the content of the dataset or created derivative work, prominent notices are made so that any recipients know that they are not receiving the original data.
  4. That you may not use or distribute the dataset or any derivative work for commercial purposes as, for example, licensing or selling the data, or using the data with a purpose to procure a commercial gain.
  5. That this original license notice is retained with all copies or derivatives of the dataset.
  6. That all rights not expressly granted to you are reserved by Daimler.

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