AI-driven interior design generation offers promising applications.However,current AI-based diffusion models struggle to generate indoor layouts in pixel-level alignment with the indoor structure.This study proposes a...AI-driven interior design generation offers promising applications.However,current AI-based diffusion models struggle to generate indoor layouts in pixel-level alignment with the indoor structure.This study proposes a new stable diffusion-based interior design workflow with an Interior Design Control Network(IDCN).IDCN ensures that the batchgenerated creative interior designs based on an input image of an unfurnished room match the indoor structure.Generating innovative designs and rendering images directly with the proposed method eliminates the tedious creative design and drawing work in traditional design practices.The results indicate that the proposed method with the new design approach achieves nearly real-time design generation and modiflcation and signiflcantly enhances design creativity and efflciency.Moreover,the proposed method can be generalized to other design generation tasks,thereby promoting the transformation toward intelligent design.展开更多
基金funded by the 2021 Nantong Science and Technology Plan Project“Research on the digital design of popularization of scientiflc knowledge”(Grant No.JCZ21074)。
文摘AI-driven interior design generation offers promising applications.However,current AI-based diffusion models struggle to generate indoor layouts in pixel-level alignment with the indoor structure.This study proposes a new stable diffusion-based interior design workflow with an Interior Design Control Network(IDCN).IDCN ensures that the batchgenerated creative interior designs based on an input image of an unfurnished room match the indoor structure.Generating innovative designs and rendering images directly with the proposed method eliminates the tedious creative design and drawing work in traditional design practices.The results indicate that the proposed method with the new design approach achieves nearly real-time design generation and modiflcation and signiflcantly enhances design creativity and efflciency.Moreover,the proposed method can be generalized to other design generation tasks,thereby promoting the transformation toward intelligent design.
