  An outfit visualization method generates an image of a person wearing real
garments from images of those garments. Current methods can produce images that
look realistic and preserve garment identity, captured in details such as
collar, cuffs, texture, hem, and sleeve length. However, no current method can
both control how the garment is worn -- including tuck or untuck, opened or
closed, high or low on the waist, etc.. -- and generate realistic images that
accurately preserve the properties of the original garment. We describe an
outfit visualization method that controls drape while preserving garment
identity. Our system allows instance independent editing of garment drape,
which means a user can construct an edit (e.g. tucking a shirt in a specific
way) that can be applied to all shirts in a garment collection. Garment detail
is preserved by relying on a warping procedure to place the garment on the body
and a generator then supplies fine shading detail. To achieve instance
independent control, we use control points with garment category-level
semantics to guide the warp. The method produces state-of-the-art quality
images, while allowing creative ways to style garments, including allowing tops
to be tucked or untucked; jackets to be worn open or closed; skirts to be worn
higher or lower on the waist; and so on. The method allows interactive control
to correct errors in individual renderings too. Because the edits are instance
independent, they can be applied to large pools of garments automatically and
can be conditioned on garment metadata (e.g. all cropped jackets are worn
closed or all bomber jackets are worn closed).
