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Rendering programs have changed the design process completely as they permitto see how the products will look before they are fabricated. However, therendering process is complicated and takes a significant amount of time, notonly in the rendering itself but in the setting of the scene as well.Materials, lights and cameras need to be set in order to get the best qualityresults. Nevertheless, the optimal output may not be obtained in the firstrender. This all makes the rendering process a tedious process. SinceGoodfellow et al. introduced Generative Adversarial Networks (GANs) in 2014[1], they have been used to generate computer-assigned synthetic data, fromnon-existing human faces to medical data analysis or image style transfer. GANshave been used to transfer image textures from one domain to another. However,paired data from both domains was needed. When Zhu et al. introduced theCycleGAN model, the elimination of this expensive constraint permittedtransforming one image from one domain into another, without the need forpaired data. This work validates the applicability of CycleGANs on styletransfer from an initial sketch to a final render in 2D that represents a 3Ddesign, a step that is paramount in every product design process. We inquirythe possibilities of including CycleGANs as part of the design pipeline, moreprecisely, applied to the rendering of ring designs. Our contribution entails acrucial part of the process as it allows the customer to see the final productbefore buying. This work sets a basis for future research, showing thepossibilities of GANs in design and establishing a starting point for novelapplications to approach crafts design.

Capabilities, Limitations and Challenges of Style Transfer with CycleGANs: A Study on Automatic Ring Design Generation