A Computational Approach to Generate Design With Specific Style

Da, Wang; Li, Jiaqi; Zhang, Ge; Han, Jiarui

doi:10.1017/pds.2021.3

Cited by 4 publications

(5 citation statements)

References 27 publications

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“…Rather than creating the initial concepts directly, AI could influence the design teams methodology and may be better suited in ICED23 populating a mood board or vision board. Research is investigating how many generative steps are required to suitably inspire a designer based on AI generated chairs (Wang et al, 2021).…”

Section: Perceptions Of the Generated Concept Imagesmentioning

confidence: 99%

Exploring the Role of Text-to-Image Ai in Concept Generation

2023

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Artificial intelligence (AI) capable of generating images from a text prompt are becoming increasingly prevalent in society and design. The general public can use their computers and mobile devices to ask a complex text-to-image AI to create an image which is in some cases indistinguishable from that which a human could create using a computer graphics package. These images are shared on social media and have been used in the creation of art projects, documents and publications. This exploratory study aimed to identify if modern text-to-image AI (Midjourney, DALL-E 2, and Disco Diffusion) could be used to replace the designer in the concept generation stage of the design process. Teams of design students were asked to evaluate AI generated concepts from 15 to a final concept. The outcomes of this research are a first of its kind for the field of engineering design, in the identification of barriers in the use of current text-to-image AI for the purpose of engineering design. The discussion suggests how this can be overcome in the short term and what knowledge the research community needs to build to overcome these barriers in the long term.

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Section: Perceptions Of the Generated Concept Imagesmentioning

confidence: 99%

Exploring the Role of Text-to-Image Ai in Concept Generation

2023

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“…The method is able to generate a variety of cross-domain conceptual associations and can have advantages in terms of the number and novelty of ideas. Based on the linear controllability of the latent space vector of StyleGAN , the researchers proposed a method for image stimulus generation with feature fusion in conceptual design (Wang et al, 2021). The process of generative stimuli generation requires that the design semantics are first understood prior to the generation of the visual display.…”

Section: Generative Image-based Ideation Approachmentioning

confidence: 99%

“…This experiment searched Google images and obtained images of horses and arches as stimuli for the image ICED23 group (Stimuli A and Stimuli C in Figure 1.). The generative stimuli come from a computational design generation method with a specific style and feature (Wang et al, 2021). The specific implementation methods are described below.…”

Section: Stimuli Preparationmentioning

confidence: 99%

“…According to cognitive psychology, people tend to produce mappings and output behaviors that are similar to the stimuli from the design resource (Howard et al, 2008). Among the types of stimuli, including verbal/textual (Shi et al 2017, Sarica et al 2023, visual/pictorial (Han et al 2018a, Wang et al 2021) and physical objects (Gonçalves et al, 2014). Pictorial stimuli are considered to be a better way of stimulating both professional and novice designers than text and objects, helping them to generate complex thinking, original solutions and sketching (Sarkar and Chakrabarti, 2008;Bettaieb, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Impact of Generative Stimuli on the Creativity of Designers in Combinational Design

Han

2023

Proc. Des. Soc.

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The ideation process has a significant impact on the initial concept generation and final product creativity of the design. Visual stimuli play an important role in the process of innovative product design. With the increase in computing capability, generative design methods are widely implemented. In this paper, features of design targets and combinational objects in 2 combinational design tasks are fused using adversarial neural generative networks to form the generated stimuli. It is also used with combinational object pictures to investigate the impact on creativity in design ideation. The study invited designers to use and subjectively self-evaluate the two stimuli in a design task. Through analysis of participant data (n=20), the results showed that the generative stimuli had an advantage over the combinational image stimuli in terms of the smoothness of creativity in the design ideation of outcomes. And there is a positive correlation between designers' years of design education and their tendency to prefer generative stimuli. Based on the results obtained, ideas are provided for the study of the influence of visual and generative stimuli on the designer's ideation process.

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“…With improved living standards, more residents aspire to personalized and exquisitely designed residences [1][2][3][4][5]. However, designers face challenges regarding insufficient creativity and cumbersome design processes when adopting traditional interior design methods [6][7][8][9][10][11]. The lack of creativity is due to the random emergence of design inspiration [6,12,13], while complex workflows decrease the design efficiency [6,14,15].…”

Section: Introduction 1background and Motivationmentioning

confidence: 99%

A New Approach to Interior Design: Generating Creative Interior Design Videos of Various Design Styles from Indoor Texture-Free 3D Models

Shao,

Chen,

Zeng

et al. 2024

Buildings

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Interior design requires designer creativity and significant workforce investments. Meanwhile, Artificial Intelligence (AI) is crucial for enhancing the creativity and efficiency of interior design. Therefore, this study proposes an innovative method to generate multistyle interior design and videos with AI. First, this study created a new indoor dataset to train an AI that can generate a specified design style. Subsequently, video generation and super-resolution modules are integrated to establish an end-to-end workflow that generates interior design videos from texture-free 3D models. The proposed method utilizes AI to produce diverse interior design videos directly, thus replacing the tedious tasks of texture selection, lighting arrangement, and video rendering in traditional design processes. The research results indicate that the proposed method can effectively provide diverse interior design videos, thereby enriching design presentation and improving design efficiency. Additionally, the proposed workflow is versatile and scalable, thus holding significant reference value for transforming traditional design toward intelligence.

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A Computational Approach to Generate Design With Specific Style

Cited by 4 publications

References 27 publications

Exploring the Role of Text-to-Image Ai in Concept Generation

Exploring the Role of Text-to-Image Ai in Concept Generation

Exploring the Impact of Generative Stimuli on the Creativity of Designers in Combinational Design

A New Approach to Interior Design: Generating Creative Interior Design Videos of Various Design Styles from Indoor Texture-Free 3D Models

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