  Sketch-to-image (S2I) translation plays an important role in image synthesis
and manipulation tasks, such as photo editing and colorization. Some specific
S2I translation including sketch-to-photo and sketch-to-painting can be used as
powerful tools in the art design industry. However, previous methods only
support S2I translation with a single level of density, which gives less
flexibility to users for controlling the input sketches. In this work, we
propose the first multi-level density sketch-to-image translation framework,
which allows the input sketch to cover a wide range from rough object outlines
to micro structures. Moreover, to tackle the problem of noncontinuous
representation of multi-level density input sketches, we project the density
level into a continuous latent space, which can then be linearly controlled by
a parameter. This allows users to conveniently control the densities of input
sketches and generation of images. Moreover, our method has been successfully
verified on various datasets for different applications including face editing,
multi-modal sketch-to-photo translation, and anime colorization, providing
coarse-to-fine levels of controls to these applications.
