  We show how to insert an object from one image to another and get realistic
results in the hard case, where the shading of the inserted object clashes with
the shading of the scene. Rendering objects using an illumination model of the
scene doesn't work, because doing so requires a geometric and material model of
the object, which is hard to recover from a single image. In this paper, we
introduce a method that corrects shading inconsistencies of the inserted object
without requiring a geometric and physical model or an environment map. Our
method uses a deep image prior (DIP), trained to produce reshaded renderings of
inserted objects via consistent image decomposition inferential losses. The
resulting image from DIP aims to have (a) an albedo similar to the
cut-and-paste albedo, (b) a similar shading field to that of the target scene,
and (c) a shading that is consistent with the cut-and-paste surface normals.
The result is a simple procedure that produces convincing shading of the
inserted object. We show the efficacy of our method both qualitatively and
quantitatively for several objects with complex surface properties and also on
a dataset of spherical lampshades for quantitative evaluation. Our method
significantly outperforms an Image Harmonization (IH) baseline for all these
objects. They also outperform the cut-and-paste and IH baselines in a user
study with over 100 users.
