The Qing Dynasty was the mature period of traditional Chinese gardens,and the construction of royal gardens reached its peak.Using the method of image and text analysis,the landscape features of different seasons in t...The Qing Dynasty was the mature period of traditional Chinese gardens,and the construction of royal gardens reached its peak.Using the method of image and text analysis,the landscape features of different seasons in the Chinese gardens were probed,the layout of its spatial elements and the method of plant landscaping was analyzed,and the artistic characteristics of the gardens in the Qing Dynasty was studied.The aesthetic conception of the gardens have been discussed from the following aspects,the integration of time and space,the harmonious relationship between the garden elements and the fusion of scenery and feelings.展开更多
Most of the existing virtual scenarios built for the digital protection of Chinese classical private gardens are too modern in expression style to show the aesthetic significance of their historical period.Considering...Most of the existing virtual scenarios built for the digital protection of Chinese classical private gardens are too modern in expression style to show the aesthetic significance of their historical period.Considering the aesthetic commonality between traditional Chinese landscape paintings and classical private gardens and referring to image style transfer,here,a deep neural network was proposed to transfer the aesthetic style from landscape paintings to the virtual scenario of classical private gardens.The network consisted of two parts:style prediction and style transfer.The style prediction network was used to obtain style representation from style paintings,and the style transfer network was used to transfer style representation to the content scenario.The pre-trained network was then embedded into the scenario rendering pipeline and combined with the screen post-processing method to realise the stylised expression of the virtual scenario.To verify the feasibility of this methodology,a virtual scenario of the Humble Administrator’s Garden was used as the content scenario andfive garden landscape paintings from different time periods and painting styles were selected for the case study.The results demonstrated that this methodology could effectively achieve the aesthetic style transfer of a virtual scenario.展开更多
基金this paper is sponsored by The National Natural Science Foundation of China(51978272)Key Projects of Guangzhou Science and Technology Plan(201804020017).
文摘The Qing Dynasty was the mature period of traditional Chinese gardens,and the construction of royal gardens reached its peak.Using the method of image and text analysis,the landscape features of different seasons in the Chinese gardens were probed,the layout of its spatial elements and the method of plant landscaping was analyzed,and the artistic characteristics of the gardens in the Qing Dynasty was studied.The aesthetic conception of the gardens have been discussed from the following aspects,the integration of time and space,the harmonious relationship between the garden elements and the fusion of scenery and feelings.
基金This work was supported by the Key Project of the National Natural Science Foundation of China(NSFC)under Grant 41930104National Key R&D Program of China under Grant 2021 YFE0112300+1 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX21_1336China Scholarship Council under Grant 202206860019.
文摘Most of the existing virtual scenarios built for the digital protection of Chinese classical private gardens are too modern in expression style to show the aesthetic significance of their historical period.Considering the aesthetic commonality between traditional Chinese landscape paintings and classical private gardens and referring to image style transfer,here,a deep neural network was proposed to transfer the aesthetic style from landscape paintings to the virtual scenario of classical private gardens.The network consisted of two parts:style prediction and style transfer.The style prediction network was used to obtain style representation from style paintings,and the style transfer network was used to transfer style representation to the content scenario.The pre-trained network was then embedded into the scenario rendering pipeline and combined with the screen post-processing method to realise the stylised expression of the virtual scenario.To verify the feasibility of this methodology,a virtual scenario of the Humble Administrator’s Garden was used as the content scenario andfive garden landscape paintings from different time periods and painting styles were selected for the case study.The results demonstrated that this methodology could effectively achieve the aesthetic style transfer of a virtual scenario.
