Graph Convolutional Network-based 3D Reconstruction of Art and Cultural Legacy

The current protection of cultural legacy faces many challenges, such as low awareness of group protection, incomplete cultural relic protection system, relatively backward protection technology, and a large shortage of professional talents in cultural relic protection. The growth of VR has provided new possibilities for the protection of cultural legacy. Virtual reality (VR) has the characteristics of multi-perception, immersion, interactivity, and conceptualization, which gives it enormous potential in the field of cultural legacy protection. This article proposes a computer-aided design (CAD) 3D reconstruction method for artistic and cultural legacy based on the Graph Convolutional Network (GCN) algorithm. By applying GCN to the 3D reconstruction of artistic and cultural legacy, it is possible to capture better and restore the details of cultural legacy and improve the effectiveness of cultural legacy reconstruction. The protection and utilization of cultural legacy is an interrelated and mutually restrictive process. Researchers need to find a reasonable balance between protection and utilization, ensuring that cultural legacy is sustainably preserved while also providing the public with a rich cultural experience. © 2024 U-turn Press LLC,.