Novel-view synthesis of human tourist photos

Jonathan Freer, Kwang Moo Yi, Wei Jiang, Jongwon Choi, Hyung Jin Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.
Original languageEnglish
Title of host publication2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
EditorsLisa O’Conner
Number of pages8
ISBN (Electronic)9781665409155
ISBN (Print)9781665409162 (PoD)
Publication statusPublished - 15 Feb 2022
EventWinter Conference on Applications of Computer Vision - Waikoloa, United States
Duration: 4 Jan 20228 Jan 2022

Publication series

NameProceedings. IEEE Workshop on Applications of Computer Vision
ISSN (Print)2642-9381
ISSN (Electronic)2642-9381


ConferenceWinter Conference on Applications of Computer Vision
Abbreviated titleWACV 2022
Country/TerritoryUnited States


  • Computational Photography
  • Image and Video Synthesis Vision for Graphics


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