Clothing Style Research Articles

Optimization Analysis of Clothing Fabric Design Based on Autoencoder and Generative Adversarial Neural Network

In order to meet the challenges of increasingly diverse clothing styles and consumer demands in the market, traditional fabric design methods have become difficult to meet the needs of rapid iteration and innovation due to their time-consuming, costly, and subjective preferences of designers. In view of this, we propose an innovative fabric design optimization simulation strategy aimed at breaking through these bottlenecks through technological means. This strategy cleverly integrates advanced technologies of variational autoencoder (VAE) and generative adversarial network (GAN). First, VAE is used to capture and learn the complex distribution characteristics of existing clothing fabric designs, which include key information such as fabric texture, color matching, and structural details. Subsequently, GAN uses the hidden vectors obtained from VAE as input to generate brand new fabric design samples. During the training phase, GAN continuously iterates and optimizes, engaging in intense “adversarial” interactions between its generator and discriminator. The generator is dedicated to creating new samples that are as close to real fabric designs as possible, while the discriminator is responsible for identifying the authenticity of these samples. This process is implemented through backpropagation (BP) loss function, ensuring that the generated fabric design can visually simulate real fabrics. Experimental verification shows that this method can not only effectively generate high-quality and realistic clothing fabric designs, but also greatly shorten the design cycle and reduce costs.

Prevalence and Determinants of Vitamin D Deficiency during the First Trimester: Evidence from a Major Metropolitan City in Bangladesh

Introduction: Vitamin D deficiency in early trimesters can have detrimental effect on feto-maternal outcomes. This research aimed to determine the prevalence and possible associated factors with vitamin D deficiency during first trimester in Chattogram city, Bangladesh. Methods: This was a cross-sectional study conducted from July to September, 2023 in Chattogram metropolitan city with purposive sampling. After obtaining consent a questionnaire was provided and blood was drawn for biochemical analysis. Statistical inference was done through SPSS V25. Results: Total 398 women participated in this study with mean age of 27 years. More than half (51.8%) were suffering subpar vitamin D level, with 15.1% being deficient and 36.7% having insufficient vitamin D level. Most participants were housewives (78.6%) with over half (57.5%) completing their undergraduate degree. Private service (40.5%) was the most prevalent spouse’s profession. Most of the women were primigravid (41.2%). 34.4% and 34.4% of participants had one instance of cesarean section and abortion respectively. High prevalence of anemia was present (49.2%) and was statistically significant with subpar vitamin D level (p<0.05). Husband’s occupation and covered clothing style was also found to be statistically significant. Conclusion: There is significant prevalence of vitamin D deficiency in early pregnancy in Chattogram metropolitan region. Further research and early intervention should be implemented to prevent and mitigate this deficiency and prevent associated adversities. J Shaheed Suhrawardy Med Coll 2023; 15(1): 39-44

Brassiere-Wearing Practices and Issues among Post-mastectomy Women: A Systematic Review

This systematic review was carried out to appraise the evidence regarding the brassiere-wearing practices and problems faced by breast cancer survivors. An electronic search was carried out across eight databases such as PubMed, Scopus, Web of Science, Science Direct, Google Scholar, Embase, CINAHL and ProQuest. Two researchers independently screened the studies for their eligibility and study quality. A total of 309 studies were assessed for eligibility. After conflict resolution by the third reviewer, five studies were selected for systematic review. All study outcomes in terms of the pattern of brassieres/prostheses, issues and challenges faced by women post-mastectomy were reviewed. It was observed that very few studies were published from various countries all over the world. All the studies were of descriptive type except one, which adopted a prospective randomised crossover design. The brassieres or prostheses, the survivors preferred were homemade made of cotton, cloth, wool, rice, sponge or commercially silicon-made. Weight of the brassiere/prostheses, discomfort, displacement while doing activities of daily living and impaired body image were common issues identified, while the unavailability of size or fit of the brassieres or requirement of alteration in clothes to meet clothing styles were common challenges faced by post-mastectomy women. It was concluded that the post- mastectomy used varied types of brassieres or prostheses with various associated issues and challenges.

Research on Intelligent Digital Manufacturing Platform Based on Artificial Intelligence Deep Neural Network

In today’s information age, intelligent manufacturing has become a significant trend of future industrial development. The neural network plays a vital role as the basis of smart manufacturing. This is a kind of intelligent algorithm that can simulate human brain organization, with strong learning ability and computing power, and has achieved remarkable results in the application field; the most typical representative is deep neural network, especially in recent years, an artificial intelligence developed based on deep neural network has entered the application stage, providing a new idea and model for industrial production. Based on this, taking the clothing production process as an example, this paper combined transfer learning and network fine-tuning technology to build a Faster RCNN model based on the ResNet-101 network to realize the positioning and recognition of clothing style map features and create an intelligent generation platform for clothing process flow on this basis.

Research on the preferences of maternity clothing shoppers

The article presents the results of a marketing study conducted to determine the preferences of buyers of clothes for expectant mothers. According to the survey results, we see the need to increase the range of comfortable, beautiful and mobile clothes for pregnant women. With the increase in the number of children, the need for clothes for women expecting a child increases every year. Naturally, expectant young mothers have a question about How to choose the right clothes during pregnancy. Women always want and strive to look stylish, appropriate and beautiful. During pregnancy, it is sometimes difficult to choose the right and beautiful clothes. So, pregnancy is a time when it is necessary to monitor the state of health for the benefit of the unborn child. Of course, during this period it is very difficult to choose clothes that will look stylish and will not harm the child's health. Maternity clothes should take into account the changed state of the body, mood, as at this time the appearance changes. To do this, in this research paper, we conducted a survey among pregnant women about which style and silhouette of clothes would be more comfortable. The results presented in our work help in the design and modeling of pregnant women's clothing.

Dress as the Agency of Power: Ozioma Onuzulike’s Ceramic Art

This study examines the ceramic works of a Nigerian artist, Ozioma Onuzulike, which vividly illustrate dress as an agency of power. His oeuvre features among other things the agbada, an extra-large clothing style prevalent in contemporary Nigeria, especially in elitist socio-political and cultural contexts. Over 25 years of Onuzulike’s ceramic art practice have consistently showcased modernist works that challenged conventional ceramic art and socio-political norms. His innovative use of clay and palm kernels to depict power dynamics in Nigeria has attracted some scholarly attention. This study employs compositional interpretation and contextual analysis to explore the visual, sociocultural, and political impact of Onuzulike’s hybrid ceramic art that depicts agbada. An iconological approach reveals the formal elements, historical, political, and social nuances embedded in the works. The concept of dress of power is used to unravel the multifaceted political significance of Onuzulike’s representations. Unpacking the visual vocabulary and metaphor of power in the works provides insights into the agbada as a status symbol in modern Nigeria. This artistic representation typifies a trend in contemporary African and diasporic art, where textile materials, forms, and ideas are central.

Creating a speech portrait of a modern Chinese teacher in online media

The purpose of the study is to identify the speech characteristics of modern Chinese teachers. The object of the study is the blog(s). Special attention is paid to the visual and auditory design of the video material: the presence of music, the design of the room, the style of the blogger's clothes, the manner of speech. The desire to show their own market attractiveness against the background of competitors, the desire to become popular and have their own audience on the Internet motivates bloggers to show authority in a variety of ways. The research material was two commercials of English language courses on the "bilibili" platform. The coronavirus infection has pushed the Chinese government and private educators to develop online teaching platforms, among which the bilibili video hosting can be cited as example. Users of this platform have the opportunity not only to watch videos, but also to purchase video courses on various topics. The work uses a descriptive method (observation, interpretation, generalization). In the course of the study, the speech analyzer programs Text-Analyzer and Cathoven were used, with the help of which the approximate level of oral text on the CEFR scale was determined. As a result of the analysis, the main features of the speech portrait of the teacher-blogger were highlighted, and the importance of the image on the Internet for attracting an audience was emphasized. The main contribution of the author is a comprehensive study of the image of a modern teacher in Chinese linguoculture. Along with the economic boom and the development of social networks in China, there has been a reassessment of traditional values. The penetration of Western mass culture has had a strong impact on the population, especially on the younger generation, who use the Internet to a greater extent and consume entertainment and educational content. This influence has not spared modern Chinese teachers. Studying the image of a Chinese teacher in modern realities will help to update information about Chinese culture, its synthesis with modern mass culture and traditional Confucian values.

Evaluating 3D Apparel Simulation Technology's Performance of Creative Pattern-Cutting Techniques with the Assist of ASVT

Three-dimensional (3D) simulation technologies have experienced a significant rise in popularity in the fashion industry. Analyzing the efficacy of such technologies aids in pinpointing areas that require enhancement. While previous studies mostly focused on evaluating the fit and appearance of 3D simulation technologies with simple clothing styles, this research aims to assess the effectiveness of 3D fashion simulation software in producing digital designs that include creative pattern-cutting techniques known for their intricate structures and design complexities. Four designs were chosen to exemplify different design characteristics, and 95 people were recruited to assess the effectiveness of two cuttingedge 3D fashion simulation programs. Furthermore, the researchers utilized the apparel spatial visualization tests (ASVT) to examine whether the participants’ spatial visualizing aptitude would impact their assessment outcomes. The findings offer suggestions for enhancing the existing 3D simulation technology and provide instructions for the assessment procedure.

Effects of Personal Values and Clothing Style Confidence on Consumers’ Interest in Upcycled Clothing Products

Effects of Personal Values and Clothing Style Confidence on Consumers’ Interest in Upcycled Clothing Products

Creating LEGO Figurines from Single Images

This paper presents a computational pipeline for creating personalized, physical LEGO ®1 figurines from user-input portrait photos. The generated figurine is an assembly of coherently-connected LEGO ® bricks detailed with uv-printed decals, capturing prominent features such as hairstyle, clothing style, and garment color, and also intricate details such as logos, text, and patterns. This task is non-trivial, due to the substantial domain gap between unconstrained user photos and the stylistically-consistent LEGO ® figurine models. To ensure assemble-ability by LEGO ® bricks while capturing prominent features and intricate details, we design a three-stage pipeline: (i) we formulate a CLIP-guided retrieval approach to connect the domains of user photos and LEGO ® figurines, then output physically-assemble-able LEGO ® figurines with decals excluded; (ii) we then synthesize decals on the figurines via a symmetric U-Nets architecture conditioned on appearance features extracted from user photos; and (iii) we next reproject and uv-print the decals on associated LEGO ® bricks for physical model production. We evaluate the effectiveness of our method against eight hundred expert-designed figurines, using a comprehensive set of metrics, which include a novel GPT-4V-based evaluation metric, demonstrating superior performance of our method in visual quality and resemblance to input photos. Also, we show our method's robustness by generating LEGO ® figurines from diverse inputs and physically fabricating and assembling several of them.

Metode Pembinaan Akhlak Berpakaian Oleh Guru Pendidikan Agama Islam di SMPN 1 Mandah Kecamatan Mandah Provinsi Riau

This study is motivated by the results of a problem found by several researchers, namely that there are some students who wear a headscarf but do not cover their breasts so that the body shape is visible, and there are also students who do not cover their genitals completely. Therefore, the teacher uses several methods to promote dress etiquette. The purpose of this study was to describe the method used by Islamic religious education teachers to promote clothing style in SMPN 1 Mandah, Mandah Regency, Riau Province. The type of research used in this study is descriptive qualitative research. The informants consisted of key informants and support informants, students and auxiliary informants, ie. Muslim religious education teachers. When gathering information through interviews, observations, and documentation. Data analysis with data reduction, data presentation and conclusion. Test the validity of the material with source triangulation, ie. comparing the results of interviews with key informants and supporting informants with the results of the author's direct observation. The results of this study are summarized as follows: that the teachers in SMPN 1 Mandah, Mandah Regency, Riau Province use several methods to promote the morals of students in dressing, namely: exemplary method, habit method, advisory method and punishment method.

Chinese consumers’ attitudes towards clothing that incorporate Chinese cultural elements: A mixed method study

In the globalized fashion market, a growing number of fashion brands and designers are utilizing Chinese cultural elements as a branding strategy to create competitive differentiation and attract Chinese consumers. Nevertheless, Chinese consumers’ attitudes towards different styles of clothing that incorporate Chinese cultural elements remain uncertain. Therefore, the present study aimed to investigate Chinese consumers’ attitudes towards clothing that incorporate Chinese cultural elements. The study also explored the factors that influence their attitudes. A mixed method approach was employed to survey 189 Chinese consumers aged 18–30. The survey encompassed attitude scales and open-ended questions. Paired samples t-tests and inductive coding were used in the data analysis. The study’s findings indicated that Chinese consumers illustrated a significantly positive attitude towards Chinese-style clothing incorporating Chinese cultural elements, compared to global-style clothing incorporating Chinese cultural elements. Moreover, five factors influence Chinese consumers’ attitudes, namely cultural experience with Chinese cultural elements, symbolism of Chinese cultural elements, nationalist sentiments, cultural aesthetics and innovation of clothing, and the harmony between the clothing style and Chinese cultural elements. Practical implications to fashion brands and fashion designers are discussed.

The underground: Alternative scenes and clothing styles in Costa Rica during the 1990s

During the 1990s, Costa Rica experienced a growth in young bands performing emergent music genres. From a post-subcultural approach, this article argues that a varied array of young bands from different musical genres and scenes created a sense of unity and support that led to the creation of what was known as ‘the underground scene’ during the 1990s. The ‘underground scene’ served as a platform that opened up a series of spaces that were alternative to the mainstream, where youth groups were able to perform their music and create new styles. In these new spaces, members of the underground developed new clothing styles linked to their musical tastes. By interviewing members of different alternative rock and reggae bands, information was gathered and analysed to visualize the development of these scenes. Members of the scene established their clothing styles based on their icons and could be identified within a specific genre due to their dress. Aesthetics were a mix of influences and bands that came directly from western countries. Americanas (thrift stores) was youth’s primary outlet for clothing hunting and they adopted current styles directly from the United States.

Modeling Realistic Clothing From a Single Image Under Normal Guide.

We propose a robust and highly realistic clothing modeling method to generate a 3D clothing model with visually consistent clothing style and wrinkles distribution from a single RGB image. Notably, this entire process only takes a few seconds. Our high-quality clothing results benefit from the idea of combining learning and optimization, making it highly robust. First, we use the neural networks to predict the normal map, a clothing mask, and a learning-based clothing model from input images. The predicted normal map can effectively capture high-frequency clothing deformation from image observations. Then, by introducing a normal-guided clothing fitting optimization, the normal maps are used to guide the clothing model to generate realistic wrinkles details. Finally, we utilize a clothing collar adjustment strategy to stylize clothing results using predicted clothing masks. An extended multi-view version of the clothing fitting is naturally developed, which can further improve the realism of the clothing without tedious effort. Extensive experiments have proven that our method achieves state-of-the-art clothing geometric accuracy and visual realism. More importantly, it is highly adaptable and robust to in-the-wild images. Further, our method can be easily extended to multi-view inputs to improve realism. In summary, our method can provide a low-cost and user-friendly solution to achieve realistic clothing modeling.

Rental Clothing site (THE BORROW TREND)

Abstract – This research paper investigates the emerging trend of clothing rental websites, examining their impact on the fashion industry, consumer behavior, and environmental sustainability. The study aims to provide a thorough literature review, propose a conceptual model for clothing rental platforms, and offer insights into the future of this innovative business model. The creation of a business model that addresses the need for affordable clothing options, particularly for special occasions like weddings. The project aims to offer a solution for individuals from lower and middle-class backgrounds who find it challenging to purchase expensive attire for events due to high costs and limited utility. By introducing a rental clothing service called “Rent Attire,” the project targets a wide audience, including lower, middle, and upper classes, with a focus on providing various styles of clothing for different occasions. The long-term goal is to become a leader in the rental clothing industry, expanding services to include event organization like weddings. Marketing strategies involve advertising in magazines, social media, and television, along with offering discounts to attract and retain customers. The project emphasizes customer satisfaction, with plans to open stalls in universities and expo centers to reach a broader market. The business model includes physical stores for order placement and rental charges based on the completion of orders. Overall, the project aims to fill a market gap by providing affordable and stylish clothing options for various customer segments, with a focus on convenience and customer service. Keywords – Rental clothing-business model,Fashion business plan, Marketing analysis, Customer need, Managing customers, Search engine optimization (SEO), Custom HTML page templates.

Парадоксы персонализации в потребительском поведении российской региональной студенческой молодежи

In consumer society, individuals have the opportunity to stand out from the crowd, for instance, through clothing and the construction of their outward appearance. However, in practice, individuals often strive not to do so, opting for clothing that allows them to blend in and become part of a significant social group. Scientists studying consumer behavior have concluded that individuals navigate between their own preferences and the demands of the group. The authors of the article sought to test this hypothesis within the community of students in Volgograd, employing a qualitative sociological method – the focus group. Eleven students from three universities in Volgograd participated in the study. The results revealed that informants preferred to conform to the norms and rules of the community, highlighting the paradoxical of individualization in the field of consumer behavior of clothing style. Some participants in the study expressed a desire to appear differently, but unfortunately, their desires remain unfulfilled, and if they are realized, it is only on rare occasions such as café visits, parties, and photography sessions. By elucidating these dynamics, this research contributes to a deeper understanding of the complexities of identity construction and consumer culture in modern society.

Traditional Chinese Clothing Style Recognition and Design Based on Deep Learning

Traditional Chinese Clothing Style Recognition and Design Based on Deep Learning

Convolutional neural network application for supply–demand matching in Zhuang ethnic clothing image classification

This study aims to design a classification technique suitable for Zhuang ethnic clothing images by integrating the concept of supply–demand matching and convolutional neural networks. Firstly, addressing the complex structure and unique visual style of Zhuang ethnic clothing, this study proposes an image resolution model based on supply–demand matching and convolutional networks. By integrating visual style and label constraints, this model accurately extracts local features. Secondly, the model’s effectiveness and resolution performance are analyzed through various performance metrics in experiments. The results indicate a significant improvement in detection accuracy at different annotation points. The model outperforms other comparative methods in pixel accuracy (90.5%), average precision (83.7%), average recall (80.1%), and average F1 score (81.2%). Next, this study introduces a clothing image classification algorithm based on key points and channel attention. Through key point detection and channel attention mechanisms, image features are optimized, enabling accurate classification and attribute prediction of Zhuang ethnic clothing. Experimental results demonstrate a notable enhancement in category classification and attribute prediction, with classification accuracy and recall exceeding 90% in top-k tasks, showcasing outstanding performance. In conclusion, this study provides innovative approaches and effective solutions for deep learning classification of Zhuang ethnic clothing images.

FashionMorph: Contextually Adaptive Clothing Replacement with CLIP, Segmentation, and Stable Diffusion

Abstract: FashionMorph represents a groundbreaking advancement in digital image manipulation, seamlessly blending advanced segmentation techniques with the language comprehension capabilities of CLIP. This innovative approach simplifies the process of precise garment replacements while ensuring the preservation of realistic textures and boundaries. By incorporating stable diffusion, FashionMorph eliminates the need for extensive training on specific clothing styles, offering users a streamlined experience in expressing their preferences through natural language prompts. This empowers users in photo editing, granting them unparalleled creative freedom. The system comprises a comprehensive pipeline designed for the identification and inpainting of clothing elements. Leveraging CLIP and CLIPSeg models for robust image analysis, FashionMorph accurately identifies clothing elements and generates corresponding masks. The inpainting process utilizes a stable diffusion pipeline, resulting in impressive image quality that surpasses the performance of notable models like DCTransformer, StyleGAN, and ADM. Evaluations based on FID and SFID scores, along with Inception Score assessments, further validate FashionMorph's effectiveness in context-aware garment editing. Visual representations of original images, inpainted results, and masks vividly demonstrate the successful outcomes achieved by FashionMorph, establishing it as an efficient and user-friendly solution for professionals and enthusiasts alike. Among the evaluated models, Stable Diffusion emerges as the standout performer, boasting remarkable FID and SFID scores of 0.35 and 0.20, respectively, indicative of its outstanding image fidelity and diversity. Conversely, DCTransformer exhibits the highest FID and SFID scores, while StyleGAN excels in diversity but falls short in FID. ADM (dropout) strikes a balance between fidelity and diversity. These results underscore the exceptional performance of Stable Diffusion, solidifying its position as the leading approach with the lowest FID and SFID values

The Artistic Expression of Character Shaping and Dramatic Costume Design

Character shaping and theatrical costume design complement each other in theatrical performance. Character shaping requires consideration of the character's background, personality traits, and goals, and showcases the character's characteristics through techniques such as dialogue, body language, and psychological description. Dramatic costume design should reflect the personality of the characters, conform to the theatrical style and historical background, and reflect the development of the characters in the plot. By selecting appropriate materials, colors, and designing clothing styles, as well as cleverly matching accessories, theatrical costumes can enhance the effect of character shaping. The interaction between characters and clothing is reflected in clothing strengthening character characteristics, assisting in expressing character emotions, and creating a suitable plot atmosphere. By integrating character shaping with theatrical costume design, the connotation of characters can be better interpreted, and the overall expressive power of drama can be enhanced.