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Removing Reflections from RAW Photos

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.

View a PDF of the paper titled Removing Reflections from RAW Photos, by Eric Kee and 3 other authors View PDF Abstract:We describe a system to remove real-world reflections from images for consumer photography. 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.

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