主催: 一般社団法人 日本機械学会
会議名: 第37回 計算力学講演会
開催日: 2024/10/18 - 2024/10/20
The incorporation of artificial intelligence (AI) into creative domains has inaugurated a new epoch of digital artistry, enabling the transformation from rudimentary sketches to fully realized figures. The current generation of AI drawing tools, which are primarily utilized as supplementary tools in the editing process, have not yet reached the level of autonomy required for autonomous image generation. In this study, we present a novel AI-driven framework that harnesses the power of Generative Adversarial Networks (GANs), a bizarre pose estimator, and Stable Diffusion models. The system accepts an anime character image as input and produces a sequence of four progressive illustrations: a corresponding skeleton, body block, muscle structure, and refined line art. The objective of this research is to develop a comprehensive system that provides novice learners with a detailed, step-by-step guide to drawing, thereby demystifying the intricate art of illustration. This initiative not only advances the field of AI in art but also provides a unique pedagogical approach that details the intermediate stages of drawing, which are often overlooked by existing applications. By enabling novices to visualize each step, our system serves to reduce the learning curve and enhance the study of drawing.