  Copying an element from a photo and pasting it into a painting is a
challenging task. Applying photo compositing techniques in this context yields
subpar results that look like a collage --- and existing painterly stylization
algorithms, which are global, perform poorly when applied locally. We address
these issues with a dedicated algorithm that carefully determines the local
statistics to be transferred. We ensure both spatial and inter-scale
statistical consistency and demonstrate that both aspects are key to generating
quality results. To cope with the diversity of abstraction levels and types of
paintings, we introduce a technique to adjust the parameters of the transfer
depending on the painting. We show that our algorithm produces significantly
better results than photo compositing or global stylization techniques and that
it enables creative painterly edits that would be otherwise difficult to
achieve.
