  We present a method to transfer the appearance of one or a few exemplar
SVBRDFs to a target image representing similar materials. Our solution is
extremely simple: we fine-tune a deep appearance-capture network on the
provided exemplars, such that it learns to extract similar SVBRDF values from
the target image. We introduce two novel material capture and design workflows
that demonstrate the strength of this simple approach. Our first workflow
allows to produce plausible SVBRDFs of large-scale objects from only a few
pictures. Specifically, users only need take a single picture of a large
surface and a few close-up flash pictures of some of its details. We use
existing methods to extract SVBRDF parameters from the close-ups, and our
method to transfer these parameters to the entire surface, enabling the
lightweight capture of surfaces several meters wide such as murals, floors and
furniture. In our second workflow, we provide a powerful way for users to
create large SVBRDFs from internet pictures by transferring the appearance of
existing, pre-designed SVBRDFs. By selecting different exemplars, users can
control the materials assigned to the target image, greatly enhancing the
creative possibilities offered by deep appearance capture.
