Reflections on glossy objects contain valuable and hidden information about the surrounding environment. By converting these objects into cameras, we can unlock exciting applications, including imaging beyond the camera's field-of-view and from seemingly impossible vantage points, e.g. from reflections on the human eye. However, this task is challenging because reflections depend jointly on object geometry, material properties, the 3D environment, and the observer viewing direction. Our approach converts glossy objects with unknown geometry into radiance-field cameras to image the world from the object's perspective. Our key insight is to convert the object surface into a virtual sensor that captures cast reflections as a 2D projection of the 5D environment radiance field visible to the object. We show that recovering the environment radiance fields enables depth and radiance estimation from the object to its surroundings in addition to beyond field-of-view novel-view synthesis, i.e. rendering of novel views that are only directly-visible to the glossy object present in the scene, but not the observer. Moreover, using the radiance field we can image around occluders caused by close-by objects in the scene. Our method is trained end-to-end on multi-view images of the object and jointly estimates object geometry, diffuse radiance, and the 5D environment radiance field.
翻译:光滑天体的反射包含关于周围环境的宝贵和隐藏的信息。 通过将这些天体转换成相机, 我们可以解开令人兴奋的应用, 包括镜头视野以外的图像, 以及似乎不可能的有利点, 例如从人眼上的反射。 然而, 这项任务具有挑战性, 因为反射同时取决于对象的几何、 物质属性、 3D 环境, 以及观察者观察方向。 我们的方法将光滑天体的不为人知的光亮- 现场相机转换成从天体的角度描绘世界的图像。 我们的关键洞察力是将天体表面转换成虚拟传感器, 将映射的映射成2D 映射出可见于天体的5D 环境的光亮场。 我们显示, 恢复环境的光亮度使得从天体到周围的深度和光亮度估计能够超越视野外观、 3D 环境的合成, 也就是说, 仅能直接看到光线光谱的物体, 而不是观察者。 此外, 利用光亮场场场, 我们可以在视野周围的视野上映像场的图像, 由经过训练的 方向 。