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 6.5 seconds on an iPhone 14 Pro. We test on RAW photos that were captured in the field and embody typical consumer photographs.

本研究描述了一种用于消费者摄影的去除真实世界反射的系统，该系统操作于线性（RAW）照片，并可选择地添加一张朝相反方向拍摄的上下文照片来消除反射干扰。该系统使用合成的真实世界RAW图像组合进行训练，利用光度学和几何上准确的反射模拟。我们的系统包括一个基础模型，接受捕获的照片和可选的上下文照片作为输入，以256p的分辨率处理，然后通过一个上采样模型将输出的256p图像转换为全分辨率。该系统在iPhone 14 Pro上可在6.5秒内生成1K分辨率的图像，我们对在实地拍摄的RAW照片进行了测试，这些照片体现了典型的消费者照片。

修复RAW照片中的反射