Saliency3D: A 3D Saliency Dataset Collected on Screen-Reference-Cited by-同舟云学术

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Saliency3D: A 3D Saliency Dataset Collected on Screen

Published:2024-06-04 Issue: Volume: Page:1-6
ISSN:
Container-title:Proceedings of the 2024 Symposium on Eye Tracking Research and Applications
language:
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Author:

Wang Yao¹^ORCID,Dai Qi²^ORCID,Bâce Mihai³^ORCID,Klein Karsten⁴^ORCID,Bulling Andreas⁵^ORCID

Affiliation:

1. Institute for Visualisation and Interactive Systems, University of Stuttgart, Germany

2. Schaeffler, China

3. Department of Computer Science, KU Leuven, Belgium

4. Life Science Informatics, University of Konstanz, Germany

5. University of Stuttgart, Germany

Funder

DFG, German Research Foundation

European Research Council (ERC)

Swiss National Science Foundation (SNSF)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3649902.3653350

Reference38 articles.

1. Roland J Baddeley and Benjamin W Tatler. 2006. High frequency edges (but not contrast) predict where we fixate: A Bayesian system identification analysis. Vision research 46, 18 (2006), 2824–2833.

2. Markus Bindemann, A Mike Burton, Ignace TC Hooge, Rob Jenkins, and Edward HF De Haan. 2005. Faces retain attention. Psychonomic bulletin & review 12, 6 (2005), 1048–1053.

3. Volker Blanz, Michael J Tarr, and Heinrich H Bülthoff. 1999. What object attributes determine canonical views?Perception 28, 5 (1999), 575–599.

4. Could the BubbleView Metaphor be used to Infer Visual Attention on 3D Graphical Content?

5. Review of Visual Saliency Detection With Comprehensive Information

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