Deep Shape and SVBRDF Estimation using Smartphone Multi-lens Imaging

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dc.contributor.authorFan, Chongruien_US
dc.contributor.authorLin, Yimingen_US
dc.contributor.authorGhosh, Abhijeeten_US
dc.contributor.editorChaine, Raphaëlleen_US
dc.contributor.editorDeng, Zhigangen_US
dc.contributor.editorKim, Min H.en_US
dc.date.accessioned2023-10-09T07:36:51Z
dc.date.available2023-10-09T07:36:51Z
dc.date.issued2023
dc.description.abstractWe present a deep neural network-based method that acquires high-quality shape and spatially varying reflectance of 3D objects using smartphone multi-lens imaging. Our method acquires two images simultaneously using a zoom lens and a wide angle lens of a smartphone under either natural illumination or phone flash conditions, effectively functioning like a single-shot method. Unlike traditional multi-view stereo methods which require sufficient differences in viewpoint and only estimate depth at a certain coarse scale, our method estimates fine-scale depth by utilising an optical-flow field extracted from subtle baseline and perspective due to different optics in the two images captured simultaneously. We further guide the SVBRDF estimation using the estimated depth, resulting in superior results compared to existing single-shot methods.en_US
dc.description.number7
dc.description.sectionheadersLearning-based Reflectance
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14972
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14972
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14972
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Computational photography; Shape inference; Reflectance modeling
dc.subjectComputing methodologies
dc.subjectComputational photography
dc.subjectShape inference
dc.subjectReflectance modeling
dc.titleDeep Shape and SVBRDF Estimation using Smartphone Multi-lens Imagingen_US
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