  Arbitrary style transfer is an important problem in computer vision that aims
to transfer style patterns from an arbitrary style image to a given content
image. However, current methods either rely on slow iterative optimization or
fast pre-determined feature transformation, but at the cost of compromised
visual quality of the styled image; especially, distorted content structure. In
this work, we present an effective and efficient approach for arbitrary style
transfer that seamlessly transfers style patterns as well as keep content
structure intact in the styled image. We achieve this by aligning style
features to content features using rigid alignment; thus modifying style
features, unlike the existing methods that do the opposite. We demonstrate the
effectiveness of the proposed approach by generating high-quality stylized
images and compare the results with the current state-of-the-art techniques for
arbitrary style transfer.
