Analysis of the formation ofNi Zan＇s landscape painting style --Taking ＂Map of a fishing village in an autumn sunny day after the rain＂ as an example

The paintings in the Yuan Dynasty, because oft.heir unique characteristics of the times, have made a deep and superexcellent track in the history of the Chinese painting, among which the literati landscape paintings represented the subject of the paintings in the Yuan Dynasty. And in the literati paintings, Ni Zan＇s paintings are the most representative. The application of the pen and ink in his works is concise and thinly scattered, and the artistic conception is cold and desolate. In this paper, with ＂Map of a fishing village in an autumn sunny day after the rain＂ as an example, the author analyzes Ni Zan＇s painting style and the causes of its formation.

APST-Flow: A Reversible Network-Based Artistic Painting Style Transfer Method

In recent years,deep generative models have been successfully applied to perform artistic painting style transfer(APST).The difficulties might lie in the loss of reconstructing spatial details and the inefficiency of model convergence caused by the irreversible en-decoder methodology of the existing models.Aiming to this,this paper proposes a Flow-based architecture with both the en-decoder sharing a reversible network configuration.The proposed APST-Flow can efficiently reduce model uncertainty via a compact analysis-synthesis methodology,thereby the generalization performance and the convergence stability are improved.For the generator,a Flow-based network using Wavelet additive coupling(WAC)layers is implemented to extract multi-scale content features.Also,a style checker is used to enhance the global style consistency by minimizing the error between the reconstructed and the input images.To enhance the generated salient details,a loss of adaptive stroke edge is applied in both the global and local model training.The experimental results show that the proposed method improves PSNR by 5%,SSIM by 6.2%,and decreases Style Error by 29.4%over the existing models on the ChipPhi set.The competitive results verify that APST-Flow achieves high-quality generation with less content deviation and enhanced generalization,thereby can be further applied to more APST scenes.

基于人工智能绘画模型STABLE DIFFUSION的椅类家具设计研究

本文基于最新的StableDiffusion人工智能绘画模型,探讨了其在家具设计领域应用的可行性。通过设计一个孔雀风格的沙发效果图,总结了该模型在家具设计中的优缺点。研究认为,StableDiffusion模型可以为设计师提供丰富的创意元素和效果图,从而大大提高了家具设计的效率和多样性。然而,该模型生成的效果图目前还比较粗糙,细节处理不足,并且具有较高的随机性。未来随着模型功能的日益完善和结合其他技术,人工智能绘画模型将成为家具设计领域重要的创意来源和设计辅助工具。

AI绘画在艺术创作中的应用——以Stable Diffusion为例

AI绘画是基于人工智能技术进行艺术创作的一种方法,在AI绘画中,Stable Diffusion可提供稳定、连续和高质量的图像生成。Stable Diffusion是一种基于生成对抗网络的图像生成方法,它通过不断更新图像的噪声分布,逐渐生成越来越逼真的图像。在绘画艺术创作中,Stable Diffusion能够激发创作者的灵感,帮助他们探索不同的创作风格和创作方式。与此同时,创作者仍需运用自己的审美判断力对所绘制的作品进行筛选和调整。

Non-Photorealistic Rendering in Chinese Painting of Animals

A set of algorithms is proposed in this paper to automatically transform 3D animal models to Chinese painting style. Inspired by real painting process in Chinese painting of animals, we divide the whole rendering process into two parts: borderline stroke making and interior shading. In borderline stroke making process we first find 3D model silhouettes in real-time depending on the viewing direction of a user. After retrieving silhouette information from all model edges, a stroke linking mechanism is applied to link these independent edges into a long stroke. Finally we grow a plain thin silhouette line to a stylus stroke with various widths at each control point and a 2D brush model is combined with it to simulate a Chinese painting stroke. In the interior shading pipeline, three stages are used to convert a Gouraud-shading image to a Chinese painting style image: color quantization, ink diffusion and box filtering. The color quantization stage assigns all pixels in an image into four color levels and each level represents a color layer in a Chinese painting. Ink diffusion stage is used to transfer inks and water between different levels and to grow areas in an irregular way. The box filtering stage blurs sharp borders between different levels to embellish the appearance of final interior shading image. In addition to automatic rendering, an interactive Chinese painting system which is equipped with friendly input devices can be also combined to generate more artistic Chinese painting images manually.

Aesthetic style transferring method based on deep neural network between Chinese landscape painting and classical private garden's virtual scenario

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.

Study on Futon Patterns in Mural of Buddhist Temple in Wutai Mountain under Digital Vision

Dao Xuan’s Gantonglu records:“About fifteen kilometers down from the southeast of the Wutai Mountain,there is the ancient Dafu Lingjiu Temple,and there are two Taoist temples in the east and west,where Buddhist matters are fulfilled.According to ancient legend,it was made by Emperor Ming of the Han Dynasty”(Daoxuan,Tang Dynasty,p.257).It can be seen that Buddhism has been introduced into Wutai Mountain since the Eastern Han Dynasty,and Buddhist temple murals have been painted on the walls of temples with the introduction of Buddhism,playing the role of spreading scriptures and decorating the walls.The pattern of Buddha’s futon base in the murals reflects the worship and rank differences of Buddhist monks in different periods.As a medium of meditation and worship,futuan is also a ritual instrument in Buddhist legend,which is of great significance.The research on the style of futon from the perspective of the frescoes in the temple of Wutai Mountain mainly focuses on the historical evolution of the frescoes and futon,the research and analysis of the base shape,pattern,composition and color of the futon in the frescoes of the temple.Explore the religious significance and historical and cultural value behind the futon style.

甘肃彩陶的几何风格迁移

甘肃彩陶在中国各类彩陶文化中拥有最为完整的时空序列,然而尚未有专门针对甘肃彩陶的风格迁移研究.为弘扬中华优秀传统文化,构建了甘肃彩陶数据集,提出了一种几何风格迁移方法.该方法生成了一个神经扭曲场,将甘肃彩陶变形为目标对象的几何风格,并保持了彩陶的纹理.网络结构方面加入了位置嵌入和特征增强模块,提高特征编码的质量.损失函数方面引入了形状一致性损失和平滑正则化项,防止彩陶的细节发生突变,提高变形效果.实验结果表明,该模型能够在甘肃彩陶与不同类的对象间进行大规模的几何风格迁移,同时可以保持良好的彩陶细节,产生新的视觉体验.

试析王维诗的禅意绘画之美

王维不仅是诗人,更是精通佛理的虔诚修士。王维的山水诗是诗中精品、艺术典范。王维诗、画兼修,画作情景交融,诗中饱含画的意蕴,画中寄寓诗的幽情,画的一切技法都可以进行诗的审美。王维的诗画清新淡远,充满禅意,造诣很高。

从汉画长袖盘鼓舞的性别形象构成说开

在汉画舞蹈中,服饰与非乐悬组合的道具舞有多种,其中长袖盘鼓舞占据了最大份额,也最具代表性。在长袖与盘鼓组合道具舞中,我们可以按男女性别形象划分出女、男、男女;其次再按表演形式划分出独舞、双人舞、三人舞、群舞。所有表演的人物、主题、结构、模态、技术和风格均可由此流出。这里的长袖包括长袖之接袖、长袖套袖之长袖、广袖套袖之长袖等,它们对盘鼓的“遮天盖地”恰好成为一个倒三角形,形成对脚下盘鼓的压制,借以脱离地球引力,振翅高飞。

从《花篮图》探讨文人风骨的画、插花和装饰应用

从李嵩的花篮图赏析起笔,以文人插花与文人画为切入点探讨中国传统文化中文人风骨的体现,将其应用于当代室内装饰中更显示出中国韵味。

浅谈工笔画元素在古风人物插画中的应用

在互联网迅速发展的今天,插画在人们的日常生活中扮演着越来越重要的角色,插画的作用已经不仅限于对书面文字的支持和补充,它已经被广泛应用到广告、动画设计、消费品等各个行业,是各个行业中常用的元素。在这样的时代大背景下,本文希望通过工笔画元素用于古风人物插画设计中所产生的视觉装饰效果来探讨中国传统工笔画的创新应用方法以及这种融合可以带给中国插画行业的发展。笔者将以市场的需求和当代中国消费者的审美理念为依托,结合案例分别从工笔画元素在古风人物插画中的应用目的以及运用方法两个方面进行分析,将中国传统工笔画的民族性通过现代设计手法与插画设计相融合,以适应当代古风人物插画设计的需求。

融合AI绘画与虚拟仿真技术的服装数字艺术风格转换与生成

通过详细分析AI绘画技术的基本原理及主要算法模型,进行了基于AI绘画与虚拟仿真技术的服装数字艺术风格转换设计,提出了一套基于AI绘画与虚拟仿真技术的服装数字艺术风格生成方法,为数字艺术和时尚设计领域提供了新的发展方向和实践路径。

汽车油漆渣VOCs释放通量预测模型的构建和验证

汽车生产过程中产生大量的油漆渣释放的VOCs会对环境和人体造成伤害.然而,关于汽车油漆渣VOCs源释放定量表征模型的研究很少.因此,本文基于非法管理场景的汽车油漆渣,建立了累积VOCs释放行为扩散控制模型.该模型具有两个关键的特征参数:扩散系数(D_(m))和初始散发浓度(C_(m,0)),可以通过我们提出的ER-history方法同时获得.材料VOCs的散发速率和浓度是关键参数的函数,测定散发关键参数是研究材料VOCs散发规律的基础.实验结果表明,1-丁醇、乙酸丁酯、1,2,4-三甲苯和1-乙基-4-甲苯是漆渣释放的主要物质.此外,利用环境测试舱的数据对模型进行了验证,证明了模型的可靠性和说服力.该模型对疏水VOCs释放的预测比亲水性VOCs的预测更准确.C_(m,0)和D_(m)的增加有促进VOCs累积释放的趋势.结果为快速测量模型参数的实验设计提供了新的见解,并为评估油漆渣VOCs累积释放提供了理论基础.

基于美学梯度法的人工智能风格化绘画系统

当前Stable diffusion等人工智能绘画模型在绘画时难以直接控制图像风格,同时风格模型训练仅针对单种风格。针对该问题,提出了一种基于美学梯度法的人工智能风格化绘画系统,以实现多种图像风格的控制和融合,并提供更加便捷的图像创作体验。收集并分析网络用户数据,结合问卷得到用户对图像风格的感性需求;根据感性需求收集各风格图像数据得到对应的风格图像训练集。使用梯度下降算法计算风格化文本编码器的权重,实现生成图像风格化的效果。通过可用性测试对比用户对该系统与传统人工智能绘画系统产出图像的风格满意程度,结果表明:人工智能风格化绘画系统的平均满意度相较传统人工智能绘画系统提升23%,表明人工智能风格化绘画系统在图像风格生成上具有更好的效果,可满足用户对图像风格的需求。该人工智能风格化绘画系统可以更便捷地实现图像风格调整,允许用户直观选择不同风格的权重,便捷使用一种或多种风格,能够有效满足用户对图像风格设计的需求。

恽寿平山水画美学分期及其在扬州地区的传播问题

在中国绘画史上被誉为“清初六大家”之一的恽寿平的“没骨花”在清代画坛上具有重要的地位与深远的影响,但他在“没骨花”广为社会认可的同时,始终没有放弃山水画的创作,并在其诗文与《南田画跋》中留下了大量关于山水画论述的内容。通过分析恽寿平山水画的笔墨特点与风格成因,可以将其发展分成三个阶段,并归纳总结出其各自的美学风格特征,同时厘清对恽寿平山水画的一些固有观点,并在此基础之上分析阐述其款识书法的分期,发现其画作在扬州地区传播遇冷的待解问题。

从特征辨识到图像生成:基于AIGC范式的苗族服饰设计

苗族服饰是中国民族服饰体系中重要的组成部分,在商品化发展中开辟了广阔的市场,但产品同质化现象将阻碍民族文化的进一步发展,人工智能生成内容(AIGC)的发展为传统服饰设计提供了新的可能。文章基于苗族服饰现代化的需要,通过搭建多模型组合流程,为苗族服饰成衣化设计提供灵感样本。实验结果表明,以服饰辨识性为基础,采用Lora训练方式,仅需少量样本即可实现苗族服饰特征在Stable Diffusion生成内容中的迁移。将深度学习引入非遗服饰现代化的进程中,旨在助力非遗服饰朝着成衣化、多样化、大众化方向发展,以数字化方式推动民族服饰转型升级。

浅析沈阳故宫东所外檐彩画样式艺术内涵

文章以沈阳故宫东所建筑外檐彩画为界定对象,从彩画的样式类型、构图规律、纹饰寓意等方面入手,采用实地调研、数字模拟等研究方法,厘清了东所各建筑外檐彩画的样式规制,科学地解读其艺术特征以及背后所蕴含的中华儒家礼制思想内涵,在理论上为沈阳故宫建筑特色的研究以及中国建筑彩画的发展情况提供补充。

《芥子园画传·初集》的编排体例及图像谱系探析

《芥子园画传·初集》是中国传统山水画技法教学的经典之作,在中国画教学史上具有重要的指导意义。《初集》采用由浅入深的编排体例,构建了兼具程式化与意象化的图像谱系,并以系统化的图像体系、标准化的技法呈现和开放性的绘画理念为中国画教学提供了全新的范式。

基于扩散模型的SUV汽车前脸风格意象研究

人工智能的最新进展正在带来一种变革性的AI驱动的产品设计方法,对许多行业产生重大影响。本文提出了一种基于运动型多用途车前脸风格意象的情感设计方法,利用扩散模型辅助生成新的造型方案,通过眼动追踪技术对生成的样本进行评估,旨在帮助设计师了解AI驱动模式下,代表不同风格意象的SUV汽车融合后,消费者对融合前后样本前脸特征关注的重点。实验结果表明:(1)有无格栅的设计会影响被试者对“时尚的”的意象感知;(2)格栅样式会影响“沉稳的”和“科技的”感知,有边框的格栅促进“沉稳的”感知,无边框格栅更易感知到“科技的”意象;(3)上扬的特征线和细长上扬的前车灯促进“时尚的”意象感知。研究结果为基于AI驱动设计不同风格产品提供了一个新的思路,增加对人工智能应用于产品设计的理解。