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CITATION.cff
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: "TORSO-21 Dataset: Typical Objects in RoboCup Soccer 2021"
message: "If you use this dataset or its related software, please cite it using the metadata from this file."
type: dataset
license: MIT
date-released: "2021-06-27"
authors:
- given-names: Marc
family-names: Bestmann
email: marc.bestmann@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-7857-793X'
- given-names: Timon
family-names: Engelke
affiliation: Universität Hamburg
email: timon.engelke@uni-hamburg.de
- given-names: Niklas
family-names: Fiedler
email: niklas.fiedler@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-0856-5087'
- given-names: Jasper
family-names: Güldenstein
email: jasper.gueldenstein@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-5416-5850'
- given-names: Jan
family-names: Gutsche
email: jan.gutsche@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-0868-8589'
- given-names: Jonas
family-names: Hagge
email: jonas.hagge@uni-hamburg.de
affiliation: Universität Hamburg
- given-names: Florian
family-names: Vahl
email: florian.vahl@uni-hamburg.de
affiliation: Universität Hamburg
identifiers:
- type: doi
value: 10.1007/978-3-030-98682-7_6
description: link.springer.com
repository-code: 'https://github.com/bit-bots/TORSO_21_dataset'
url: 'https://github.com/bit-bots/TORSO_21_dataset'
abstract: >-
We present a dataset specifically designed to be
used as a benchmark to compare vision systems in
the RoboCup Humanoid Soccer domain. The dataset is
composed of a collection of images taken in various
real-world locations as well as a collection of
simulated images. It enables comparing vision
approaches with a meaningful and expressive metric.
The contributions of this paper consist of
providing a comprehensive and annotated dataset, an
overview of the recent approaches to vision in
RoboCup, methods to generate vision training data
in a simulated environment, and an approach to
increase the variety of a dataset by automatically
selecting a diverse set of images from a larger
pool. Additionally, we provide a baseline of YOLOv4
and YOLOv4-tiny on this dataset.
keywords:
- Computer vision
- Vision dataset
- Deep learning
preferred-citation:
title: "TORSO-21 Dataset: Typical Objects in RoboCup Soccer 2021"
type: conference-paper
authors:
- given-names: Marc
family-names: Bestmann
email: marc.bestmann@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-7857-793X'
- given-names: Timon
family-names: Engelke
affiliation: Universität Hamburg
email: timon.engelke@uni-hamburg.de
- given-names: Niklas
family-names: Fiedler
email: niklas.fiedler@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-0856-5087'
- given-names: Jasper
family-names: Güldenstein
email: jasper.gueldenstein@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-5416-5850'
- given-names: Jan
family-names: Gutsche
email: jan.gutsche@uni-hamburg.de
affiliation: Universität Hamburg
orcid: 'https://orcid.org/0000-0002-0868-8589'
- given-names: Jonas
family-names: Hagge
email: jonas.hagge@uni-hamburg.de
affiliation: Universität Hamburg
- given-names: Florian
family-names: Vahl
email: florian.vahl@uni-hamburg.de
affiliation: Universität Hamburg
doi: "10.1007/978-3-030-98682-7_6"