Novel-View Synthesis of Human Tourist Photos
- Authors
- Freer, J.; Yi, K.M.; Jiang, W.; Choi, Jongwon; Chang, H.J.
- Issue Date
- Jan-2022
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Computational Photography; Image and Video Synthesis Vision for Graphics
- Citation
- Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022, pp 857 - 864
- Pages
- 8
- Journal Title
- Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022
- Start Page
- 857
- End Page
- 864
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/61736
- DOI
- 10.1109/WACV51458.2022.00093
- ISSN
- 0000-0000
- Abstract
- We present a novel framework for performing novel-view synthesis on human tourist photos. Given a tourist photo from a known scene, we reconstruct the photo in 3D space through modeling the human and the background independently. We generate a deep buffer from a novel viewpoint of the reconstruction and utilize a deep network to translate the buffer into a photo-realistic rendering of the novel view. We additionally present a method to relight the renderings, allowing for relighting of both human and background to match either the provided input image or any other. The key contributions of our paper are: 1) a framework for performing novel view synthesis on human tourist photos, 2) an appearance transfer method for relighting of humans to match synthesized backgrounds, and 3) a method for estimating lighting properties from a single human photo. We demonstrate the proposed framework on photos from two different scenes of various tourists. © 2022 IEEE.
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- Appears in
Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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