ACRV Robotic Vision Challenge 1 CVPR 2019 Test data
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This is the test data for the first Australian Centre for Robotic Vision (ACRV) Robotic Vision Challenge. It consists of 18 rendered video sequences, in which participants must detect objects, with both spatial and semantic uncertainty.
For more details, see https://competitions.codalab.org/competitions/20940.
The sequence contains synthetic data generated using Unreal Engine 4. For more details on its generation, see the workshop paper: https://arxiv.org/abs/1903.07840.
Data files consist of 18 zip files, each containing a video sequence made up of multiple .png images.
Contact: contact@roboticvisionchallenge.org.
Geographical area of data collection
kmlPolyCoords
153.028415,-27.477357
Publications
Probabilistic Object Detection: Definition and Evaluation by David Hall, Feras Dayoub, John Skinner, Haoyang Zhang, Dimity Miller, Peter Corke, Gustavo Carneiro, Anelia Angelova, Niko Sünderhauf. 10 April 2019
https://arxiv.org/abs/1811.10800v3
The Probabilistic Object Detection Challenge by John Skinner, David Hall, Haoyang Zhang, Feras Dayoub, Niko Sunderhauf. 19 March 2019.
https://arxiv.org/abs/1903.07840
Research areas
Computer
Vision
Simulation
and
Modelling
Control
Systems,
Robotics
and
Automation
Cite this collection
ARC Centre of Excellence in Robotic Vision (2019): ACRV Robotic Vision Challenge 1 CVPR 2019 Test data. Queensland University of Technology. (Image) https://doi.org/10.25912/5ca3e5a01c255
Related information
Further challenge information
http://www.roboticvisionchallenge.org/
Access the data
Licence
Copyright
© ARC Centre of Excellence in Robotic Vision, 2018.
Dates of data collection
From 10-12-2018 to 12-12-2018
Connections
Has association with
Is output of
Contacts
Other
Date record created:
2019-04-02T10:12:07
Date record modified:
2019-04-12T13:52:14
Record status:
Published - Open Access