Interactive Co-Creation with StyleGAN for Enhancing Visual Design Using Generative AI

The integration of artificial intelligence (AI) into creative workflows has significantly transformed digital media design, enabling more efficient and innovative processes. This study proposes an interactive co-creation framework driven by StyleGAN2-ADA, designed to enhance human-AI collaboration in visual content generation. The purpose of the research is to evaluate the potential of AI-assisted ideation in creative industries, focusing on the development of a real-time system that allows users to manipulate semantic visual attributes such as expression, style intensity, and lighting. A total of 18 participants, including design professionals and students, engaged with the system to perform creative tasks, providing both quantitative and qualitative data on system usability and effectiveness. The study utilized Fréchet Inception Distance (FID), System Usability Scale (SUS), and interaction logs to measure image quality, user satisfaction, and engagement. Key findings include a low FID score of 4.82, an average task completion time of 6.2 minutes, and a SUS score of 84.1, indicating high usability and efficiency. User feedback highlighted the system’s ability to facilitate rapid ideation and foster a productive balance between AI assistance and creative autonomy. The findings suggest that the proposed framework can serve as an effective tool for enhancing the creative process, with potential applications in design, education, and multimedia systems. Future research will explore expanding the framework’s applicability to diverse creative tasks and further improving user interaction features.