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Computer Science > Computer Vision and Pattern Recognition

arXiv:2404.14414 (cs)
[Submitted on 28 Feb 2024 (v1), last revised 24 Apr 2024 (this
version, v2)]

Title:Removing Reflections from RAW Photos

Authors:Eric Kee, Adam Pikielny, Kevin Blackburn-Matzen, Marc Levoy
View a PDF of the paper titled Removing Reflections from RAW Photos,
by Eric Kee and 3 other authors
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    Abstract:We describe a system to remove real-world reflections
    from images for consumer photography. Our system operates on
    linear (RAW) photos, with the (optional) addition of a contextual
    photo looking in the opposite direction, e.g., using the selfie
    camera on a mobile device, which helps disambiguate what should
    be considered the reflection. The system is trained using
    synthetic mixtures of real-world RAW images, which are combined
    using a reflection simulation that is photometrically and
    geometrically accurate. Our system consists of a base model that
    accepts the captured photo and optional contextual photo as
    input, and runs at 256p, followed by an up-sampling model that
    transforms output 256p images to full resolution. The system can
    produce images for review at 1K in 4.5 to 6.5 seconds on a
    MacBook or iPhone 14 Pro. We test on RAW photos that were
    captured in the field and embody typical consumer photographs.

Comments: 14 pages plus 22 pages of supplemental material
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as:  arXiv:2404.14414 [cs.CV]
          (or arXiv:2404.14414v2 [cs.CV] for this version)
          https://doi.org/10.48550/arXiv.2404.14414
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Eric Kee [view email]
[v1] Wed, 28 Feb 2024 19:07:49 UTC (37,709 KB)
[v2] Wed, 24 Apr 2024 16:36:47 UTC (44,530 KB)
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