Amazing stuff! What a challenge!
"... Their method uses reflections to turn glossy objects into “cameras,” enabling a user to see the world as if they were looking through the “lenses” of everyday objects ...
This distortion depends on the shape of the object and the world that object is reflecting, both of which researchers may have incomplete information about. In addition, the glossy object may have its own color and texture that mixes with reflections. Plus, reflections are two-dimensional projections of a three-dimensional world, which makes it hard to judge depth in reflected scenes. ..."
This distortion depends on the shape of the object and the world that object is reflecting, both of which researchers may have incomplete information about. In addition, the glossy object may have its own color and texture that mixes with reflections. Plus, reflections are two-dimensional projections of a three-dimensional world, which makes it hard to judge depth in reflected scenes. ..."
From the abstract:
"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."
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