02289nas a2200325   4500000000100000008004100001653001400042653001800056653001900074653003600093653002000129653002500149653003400174653002800208653002300236653002600259653002100285653004000306653003100346653003000377100001700407700001600424700001600440700001300456245010500469856014700574490000900721520121300730022002001943                                       d10a3D models10aData handling10aDisplay system10aGenerative adversarial networks10aHigh resolution10aImage reconstruction10aIntangible cultural heritages10aOptical resolving power10aProcessing modules10aQuadratic programming10aSystem functions10aThree dimensional computer graphics10aThree dimensional displays10aThree-dimensional display1 aJiachun Wang1 aJunkui Song1 aYizhe Zhang1 aHao Chen00aDesign of 3D Display System for Intangible Cultural Heritage Based on Generative Adversarial Network  uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85135274699&doi=10.1155%2f2022%2f2944750&partnerID=40&md5=2844461d52d68f4b90892eae861d381a0 v20223 aThis paper designs a three-dimensional display system for intangible cultural heritage based on generative adversarial networks. The system function is realized through four modules: input module, data processing module, 3D model generation module, and model output module. Two 3D model reconstruction methods are used to realize the transformation from 2D images to 3D models. In the low-resolution Nuo surface 3D construction, multiresidual dense blocks are introduced and applied to the deep image super-resolution network. The experimental comparison results show that the quadratic optimization multifusion 3D construction model proposed in this paper can achieve considerable improvement and can improve the reconstruction accuracy by about 6.3\%. In the high-resolution 3D construction of the Nuo surface, a generative adversarial network model is used to improve the generator, discriminator, and loss function of the original SRGAN model. Experimental results show that this method can generate super-resolution images with more realistic and natural depth maps. In addition, when it is used for high-resolution 3D Nuo surface sculpting, it can also generate 3D voxel Nuo surfaces with more details.  a10589244 (ISSN)