Search Results (4)

Style transfer technology has seen substantial attention in image synthesis, notably in applications like oil painting, digital printing, and Chinese landscape painting. However, it is often difficult to generate migrated images that retain the essence of paper-cutting art and have strong visual appeal when trying to apply the unique style of Chinese paper-cutting art to style transfer. Therefore, this paper proposes a new method for Chinese paper-cutting style transformation based on the Transformer, aiming at realizing the efficient transformation of Chinese paper-cutting art styles. Specifically, the network consists of a frequency-domain mixture block and a multi-level feature contrastive learning module. The frequency-domain mixture block explores spatial and frequency-domain interaction information, integrates multiple attention windows along with frequency-domain features, preserves critical details, and enhances the effectiveness of style conversion. To further embody the symmetrical structures and hollowed hierarchical patterns intrinsic to Chinese paper-cutting, the multi-level feature contrastive learning module is designed based on a contrastive learning strategy. This module maximizes mutual information between multi-level transferred features and content features, improves the consistency of representations across different layers, and thus accentuates the unique symmetrical aesthetics and artistic expression of paper-cutting. Extensive experimental results demonstrate that the proposed method outperforms existing state-of-the-art approaches in both qualitative and quantitative evaluations. Additionally, we created a Chinese paper-cutting dataset that, although modest in size, represents an important initial step towards enriching existing resources. This dataset provides valuable training data and a reference benchmark for future research in this field. Full article

The artistic expression inherent in Chinese paintings serves as a conduit for the artists’ emotional and cognitive expression. However, current research lacks consensus regarding the distinct psychological mechanisms underlying the appreciation of Chinese painting genres (landscape vs. figure paintings). This study—employing a vocabulary generation task and the Implicit Association Test (IAT) to compare semantic representation and emotional awareness during participants’ viewing these two types of paintings—aims to elucidate potential disparities in aesthetic processing. In Experiment 1, although both types of paintings produced an abundance of content words, figure paintings elicited a greater number of emotional association words than landscape paintings. Meanwhile, Experiment 2 demonstrated faster response times for an incompatible joint task versus a compatible joint task. These findings collectively suggest that the aesthetic of paintings may engage automatic processes, with the effects on semantic representation and emotional awareness appearing to be independent of the type of paintings. The predominance of content processing over emotional response may be attributed to the temporal characteristics of emotional arousal. Full article

As one of the precious cultural heritages, Chinese landscape painting has developed unique styles and techniques. Researching the intelligent generation of Chinese landscape paintings from photos can benefit the inheritance of traditional Chinese culture. To address detail loss, blurred outlines, and poor style transfer in present generated results, a model for generating Chinese landscape paintings from photos named Paint-CUT is proposed. In order to solve the problem of detail loss, the SA-ResBlock module is proposed by combining shuffle attention with the resblocks in the generator, which is used to enhance the generator’s ability to extract the main scene information and texture features. In order to solve the problem of poor style transfer, perceptual loss is introduced to constrain the model in terms of content and style. The pre-trained VGG is used to extract the content and style features to calculate the perceptual loss and, then, the loss can guide the model to generate landscape paintings with similar content to landscape photos and a similar style to target landscape paintings. In order to solve the problem of blurred outlines in generated landscape paintings, edge loss is proposed to the model. The Canny edge detection is used to generate edge maps and, then, the edge loss between edge maps of landscape photos and generated landscape paintings is calculated. The generated landscape paintings have clear outlines and details by adding edge loss. Comparison experiments and ablation experiments are performed on the proposed model. Experiments show that the proposed model can generate Chinese landscape paintings with clear outlines, rich details, and realistic style. Generated paintings not only retain the details of landscape photos, such as texture and outlines of mountains, but also have similar styles to the target paintings, such as colors and brush strokes. So, the generation quality of Chinese landscape paintings has improved. Full article

New buildings continue to be constructed in historic districts as urbanization accelerates. This leads to incongruities between historic and modern buildings, as well as degradation of the historic landscape. As a means of resolving these problems, this study uses the expert scoring method to solicit opinions from relevant experts through anonymous methods for architectural samples and establishes two groups of architectural images that have been screened for objective color attribute analysis. Comparing the architectural color codes on site was conducted using the Chinese Architectural Color Card based on the Munsell color system. Furthermore, questionnaires were used to measure the differences in visual comfort between different building types by asking the subjects to rate architectural colors when viewing architectural images. This study will also combine the advantages of measurement and analysis of objective objects with the study of human perceptual experience in order to enhance its practicality. In general, the buildings in the West Nanjing Road Historic Landscape District are painted in warm yellow, and the public is aware of its comforting color. Both historical and modern buildings in the historic district are mostly of medium and high brightness, and both use low-purity colors for the main body of their structures. Despite some differences between people of different genders, ages, and literacy levels, all of them agree on the main tone of warm yellow color in architectural colors. Full article