ILSH: The imperial light-stage head dataset for human head view synthesis
Author(s)
Zheng, Jiali
Jang, Youngkyoon
Papaioannou, Athanasios
Kampouris, Christos
Potamias, Rolandos Alexandros
Type
Conference Paper
Abstract
This paper introduces the Imperial Light-Stage Head (ILSH) dataset, a novel light-stage-captured human head dataset designed to support view synthesis academic challenges for human heads. The ILSH dataset is intended to facilitate diverse approaches, such as scene-specific or generic neural rendering, multiple-view geometry, 3D vision, and computer graphics, to further advance the development of photo-realistic human avatars. This paper details the setup of a light-stage specifically designed to capture high-resolution (4K) human head images and describes the process of addressing challenges (preprocessing, ethical issues) in collecting high-quality data. In addition to the data collection, we address the split of the dataset into train, validation, and test sets. Our goal is to design and support a fair view synthesis challenge task for this novel dataset, such that a similar level of performance can be maintained and expected when using the test set, as when using the validation set. The ILSH dataset consists of 52 subjects captured using 24 cameras with all 82 lighting sources turned on, resulting in a total of 1,248 close-up head images, border masks, and camera pose pairs.
Date Issued
2023-12-25
Date Acceptance
2023-10-01
Citation
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023, pp.1104-1112
ISSN
2473-9936
Publisher
IEEE
Start Page
1104
End Page
1112
Journal / Book Title
Proceedings of the IEEE/CVF International Conference on Computer Vision
Copyright Statement
Copyright © 2023, IEEE. This ICCV workshop paper is the Open Access version, provided by the Computer Vision Foundation. Except for this watermark, it is identical to the accepted version; the final published version of the proceedings is available on IEEE Xplore.
Source
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Subjects
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Imaging Science & Photographic Technology
Computer Science
Publication Status
Published
Start Date
2023-10-02
Finish Date
2023-10-06
Coverage Spatial
Paris, France