Research on brush generation oil painting algorithm based on DCGAN-RBCA

In light of advancements in artificial intelligence, employ in light of advancements in artificial intelligence, employ to convert ordinary images into those employing deep learning methodologies to convert ordinary images into those resembling oil paintings, featuring brushstroke details, is highly significant for research. This approach aims at enabling computers to emulate the actual process of creating oil artworks. A brush-based oil painting generation algorithm, utilizing A brush-based oil painting generation algorithm, utilizing a DCGAN-RBCA (DCGAN-Generator with Residual Block and Channel Attention) neural renderer, which is proposed to enhance the precision of computer program-generated strokes and the overall quality of digital oil paintings. Subsequently, a series of comparative analyses are executed from various perspectives. The findings from the experiment indicate that the DCGAN-RBCA neural rendering model developed in this work exhibits enhanced stroke production capabilities and is capable of creating top-notch oil painting style effects.