Analysis of the Use and Effectiveness of Artificial Intelligence-Assisted Creation Tools in Digital Art and Design

Abstract

This paper focuses on the practical application of artificial intelligence-assisted creation tools in digital art design, and establishes a digital art model based on 3D animation special effects production technology. The envelope contour detection method and chunk fusion processing technology are used to optimize the 3D modeling process, and the improved HFRA-SRGAN deep learning model is used to achieve super-resolution reconstruction of digital art images. Through comparative experiments, the proposed method is verified to have significant advantages in peak signal-to-noise ratio, screen resolution, collision performance and reconstruction effect. Based on the results of user emotion annotation for digital art image design, user satisfaction is analyzed. The images reconstructed by this paper's method are more in line with human subjective vision, and the global reconstruction quality and detail reconstruction artistry scores reach 4.82 and 4.38, respectively, which are 23.9% and 29.6% higher than the sub-optimal performance of the control method2. User satisfaction scores at the instinctive, behavioral, and reflective levels all exceeded 4.5.