IEEE Conference on Virtual Reality (IEEE VR)
2nd Workshop
Data4XR
Datasets for Developing Intelligent XR Applications
Hybrid event - March 25-29, 2023
Introduction
Whenever AI researchers want to propose different data-driven models, datasets are the most fundamental resources. With easy access to standard datasets, they can develop state-of-the-art AI algorithms to achieve excellent prediction performance. However, when XR researchers decide to import these algorithms for developing intelligent immersive interactive applications, the lack of publicly available datasets arises as a challenge despite advanced AI algorithms being developed.
Many works related to datasets have been published, e.g., MINIST, ImageNet, CIFAR-10, etc. To unleash the full power of XR, the community also needs standard datasets for developing data-driven models with machine/deep learning. The workshop on Datasets for Developing Intelligent XR Applications (Data4XR), hosted by the IEEE VR 2023, proposes a meaningful platform for domain researchers to find valuable resources and develop collaborations across labs. It aims to promote XR research by involving artificial intelligence.
Scope
The workshop invites researchers to submit 1) technical papers aimed towards introducing their published datasets that can be easily accessed and used to develop data-driven models, 2) position papers describing ethics, early-stage concepts, preliminary ideas for sharable datasets creation and standardization, 3) research papers that integrate data-driven models into XR studies. The submission can be 4-6 pages on any of the following topics but not limited to:
Multisensory interfaces and rendering
Multimodal/cross-modal interaction, perception, and cognition
3D user interaction and experience
Intelligent concurrent engineering
Digital twin model use cases
Interactive simulation models and algorithms
Adaptive VR/AR interaction frameworks
Interactive reasoning for intelligent user interaction feedback in VR/AR
Human factors and ergonomics
User modeling and computational interaction
Data ethics and protection in XR
Invited Speaker
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Important dates
Submission deadline - January 9, 2023
Notification - January 20, 2023
Camera ready deadline - February 3, 2023
Workshop date - March 25-29, 2023 (to be adjusted)
Submission Guidelines
All paper submissions must be in English and must comprise 6 pages maximum, NOT including references. All Data4XR Workshop Paper submissions must be prepared in IEEE Computer Society VGTC format (http://junctionpublishing.org/vgtc/Tasks/camera.html) and submitted in PDF format. We highly encourage authors to use the LaTeX template. However, authors who choose to use the MS Word template should ensure that the PDF submission matches the PDF format template (http://junctionpublishing.org/vgtc/Templates/october2017/vgtc_conference_latex.pdf).
A DOUBLE-BLIND review process will be used. This means that both the authors and the reviewers should remain anonymous to each other. Submissions (including citations) should not contain information that identifies the authors, their institutions, funding sources, or their places of work. Relevant previous work by the authors should be cited in the third person to preserve anonymity. Authors should work diligently to ensure that their submissions do not expose their identities either through carelessness or intentionality. Authors that have questions/issues around double-blind submission policy should contact the conference chairs at the above-mentioned email address.
IEEE VR Workshops proceedings will be published electronically through the IEEE Digital Library.
NOTE: papers rejected from the IEEE VR conference track are encouraged to be resubmitted if they can fit the topic of this workshop. In this case, the authors have to submit 1) the revised version of the paper, 2) the review report from the conference reviewers, 3) one page summary of rebuttal.
Organizing Committee
Yuyang WANG
Hong Kong University of Science and Technology, China
Jean-Rémy CHARDONNET
Arts et Métiers Institute of Technology, France
Lik-Hang (Paul) LEE
Korea Advanced Inst. of Science and Technology, Korea
Pan HUI
Hong Kong University of Science and Technology, China
Contacts
If you have any questions, please contact Yuyang Wang (yuyangwang[at]ust.hk), Jean-Rémy Chardonnet (jean-remy.chardonnet[at]ensam.eu), Lik-Hang (Paul) Lee (likhang.lee[at]kaist.ac.kr) or Pan Hui (panhui[at]ust.hk).