  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.
