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We propose a novel style transfer method to quickly create a new visualproduct with a nice appearance for industrial designers' reference. Given asource product, a target product, and an art style image, our method produces aneural warping field that warps the source shape to imitate the geometric styleof the target and a neural texture transformation network that transfers theartistic style to the warped source product. Our model, Industrial StyleTransfer (InST), consists of large-scale geometric warping (LGW) andinterest-consistency texture transfer (ICTT). LGW aims to explore anunsupervised transformation between the shape masks of the source and targetproducts for fitting large-scale shape warping. Furthermore, we introduce amask smoothness regularization term to prevent the abrupt changes of thedetails of the source product. ICTT introduces an interest regularization termto maintain important contents of the warped product when it is stylized byusing the art style image. Extensive experimental results demonstrate that InSTachieves state-of-the-art performance on multiple visual product design tasks,e.g., companies' snail logos and classical bottles (please see Fig. 1). To thebest of our knowledge, we are the first to extend the neural style transfermethod to create industrial product appearances. Project page:\ulr{https://jcyang98.github.io/InST/home.html}. Code available at:\url{https://github.com/jcyang98/InST}.

Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation