• Title/Summary/Keyword: AI Painting

Search Result 23, Processing Time 0.02 seconds

Comparative Analysis of AI Painting Using [Midjourney] and [Stable Diffusion] - A Case Study on Character Drawing -

  • Pingjian Jie;Xinyi Shan;Jeanhun Chung
    • International Journal of Advanced Culture Technology
    • /
    • v.11 no.2
    • /
    • pp.403-408
    • /
    • 2023
  • The widespread discussion of AI-generated content, fueled by the emergence of consumer applications like ChatGPT and Midjourney, has attracted significant attention. Among various AI applications, AI painting has gained popularity due to its mature technology, user-friendly nature, and excellent output quality, resulting in a rapid growth in user numbers. Midjourney and Stable Diffusion are two of the most widely used AI painting tools by users. In this study, the author adopts a perspective that represents the general public and utilizes case studies and comparative analysis to summarize the distinctive features and differences between Midjourney and Stable Diffusion in the context of AI character illustration. The aim is to provide informative material forthose interested in AI painting and lay a solid foundation for further in-depth research on AI-generated content. The research findings indicate that both software can generate excellent character images but with distinct features.

Research on art contents based on 4th industrial technology -Focusing on artificial intelligence painting and NFT art- (4차 산업 기술 기반의 예술 콘텐츠 연구 -인공지능 회화와 NFT 미술을 중심으로-)

  • Bang Jinwon
    • The Journal of the Convergence on Culture Technology
    • /
    • v.10 no.4
    • /
    • pp.613-625
    • /
    • 2024
  • This study analyzed the convergence case of AI painting and NFT art, art content created based on digital technology, an innovative technology of the 4th industrial technology, and explored its characteristics. Digital technology that innovates the paradigm of life in the 21st century is being used in creative art, and AI painting and NFT art that use it as an expression tool are changing the way they perceive and accept art. AI painting using big data and artificial intelligence technology is evolving into interactive daily art, and NFT art using blockchain and NFT technology is becoming the art of the metaverse with economic and cultural values. Therefore, this study attempted to explore various aspects and values of these digital convergence arts. For the study, representative examples of AI painting and NFT art were classified into cognitive creative AI painting and language generative AI, art economic NFTs, and art and cultural NFTs, and their characteristics, contents, and meanings were analyzed. It is hoped that the results of this study will contribute to the development of AI painting and NFT art, which are digital convergence arts.

A Case Study of Creative Art Based on AI Generation Technology

  • Qianqian Jiang;Jeanhun Chung
    • International journal of advanced smart convergence
    • /
    • v.12 no.2
    • /
    • pp.84-89
    • /
    • 2023
  • In recent years, with the breakthrough of Artificial Intelligence (AI) technology in deep learning algorithms such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAE), AI generation technology has rapidly expanded in various sub-sectors in the art field. 2022 as the explosive year of AI-generated art, especially in the creation of AI-generated art creative design, many excellent works have been born, which has improved the work efficiency of art design. This study analyzed the application design characteristics of AI generation technology in two sub fields of artistic creative design of AI painting and AI animation production , and compares the differences between traditional painting and AI painting in the field of painting. Through the research of this paper, the advantages and problems in the process of AI creative design are summarized. Although AI art designs are affected by technical limitations, there are still flaws in artworks and practical problems such as copyright and income, but it provides a strong technical guarantee in the expansion of subdivisions of artistic innovation and technology integration, and has extremely high research value.

Research on AI Painting Generation Technology Based on the [Stable Diffusion]

  • Chenghao Wang;Jeanhun Chung
    • International journal of advanced smart convergence
    • /
    • v.12 no.2
    • /
    • pp.90-95
    • /
    • 2023
  • With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

A Study on AI Softwear [Stable Diffusion] ControlNet plug-in Usabilities

  • Chenghao Wang;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.15 no.4
    • /
    • pp.166-171
    • /
    • 2023
  • With significant advancements in the field of artificial intelligence, many novel algorithms and technologies have emerged. Currently, AI painting can generate high-quality images based on textual descriptions. However, it is often challenging to control details when generating images, even with complex textual inputs. Therefore, there is a need to implement additional control mechanisms beyond textual descriptions. Based on ControlNet, this passage describes a combined utilization of various local controls (such as edge maps and depth maps) and global control within a single model. It provides a comprehensive exposition of the fundamental concepts of ControlNet, elucidating its theoretical foundation and relevant technological features. Furthermore, combining methods and applications, understanding the technical characteristics involves analyzing distinct advantages and image differences. This further explores insights into the development of image generation patterns.

State Visualization Design of AI Speakers using Color Field Painting (색면추상 기법을 통한 AI 스피커의 상태 시각화 디자인 연구)

  • Hong, Seung Yoon;Choe, Jong-Hoon
    • The Journal of the Korea Contents Association
    • /
    • v.20 no.2
    • /
    • pp.572-580
    • /
    • 2020
  • Recently released AI speakers show a pattern of interacting with the user by mainly with voice and simultaneously displaying simple and formal visual feedback through status LED light. This is due to the limitations of the product characteristics of the speaker, which makes it difficult to interact variously, and even such visual feedback is not standardized for each product, and thus does not give a consistent user experience. By maximizing the visual elements that can be expressed through color and abstract movement to assist voice feedback, the product can provide the user with an extended experience that includes not only functional satisfaction but also emotional satisfaction. In this study, after analyzing the interaction methods of the existing AI speakers, we examined the theory of color communication in order to expand the visual feedback effect, and examined the meaning and expression technique of Color Field Painting, an art genre that maximizes the emotional experience by using only color. Through this, the AI speaker's visual communication function was expanded by designing a way to feedback communication status using LED light.

AI Art Creation Case Study for AI Film & Video Content (AI 영화영상콘텐츠를 위한 AI 예술창작 사례연구)

  • Jeon, Byoungwon
    • The Journal of the Convergence on Culture Technology
    • /
    • v.7 no.2
    • /
    • pp.85-95
    • /
    • 2021
  • Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

A Research on AI Generated 2D Image to 3D Modeling Technology

  • Ke Ma;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.16 no.2
    • /
    • pp.81-86
    • /
    • 2024
  • Advancements in generative AI are reshaping graphic and 3D content design landscapes, where AI not only enriches graphic design but extends its reach to 3D content creation. Though 3D texture mapping through AI is advancing, AI-generated 3D modeling technology in this realm remains nascent. This paper presents AI 2D image-driven 3D modeling techniques, assessing their viability in 3D content design by scrutinizing various algorithms. Initially, four OBJ model-exporting AI algorithms are screened, and two are further evaluated. Results indicate that while AI-generated 3D models may not be directly usable, they effectively capture reference object structures, offering substantial time savings and enhanced design efficiency through manual refinements. This endeavor pioneers new avenues for 3D content creators, anticipating a dynamic fusion of AI and 3D design.

Research on Character's Consistency in AI-Generated Paintings

  • Chenghao Wang;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.16 no.3
    • /
    • pp.199-204
    • /
    • 2024
  • This study aims to explore the issue of character consistency in AI-generated artwork. First, the concept of character consistency is explained, including the consistency of appearance, actions, and lighting, and its importance in continuous creation and storytelling is analyzed. Next, the study examines current mainstream AI drawing tools such as MidJourney and Stable Diffusion-based WebUI and ComfyUI, evaluating their strengths and limitations in maintaining character consistency. Finally, methods to improve AI drawing technology were proposed to enhance character consistency, aiming to achieve a higher level of consistency in AI art creation.

A Research on Aesthetic Aspects of Checkpoint Models in [Stable Diffusion]

  • Ke Ma;Jeanhun Chung
    • International journal of advanced smart convergence
    • /
    • v.13 no.2
    • /
    • pp.130-135
    • /
    • 2024
  • The Stable diffsuion AI tool is popular among designers because of its flexible and powerful image generation capabilities. However, due to the diversity of its AI models, it needs to spend a lot of time testing different AI models in the face of different design plans, so choosing a suitable general AI model has become a big problem at present. In this paper, by comparing the AI images generated by two different Stable diffsuion models, the advantages and disadvantages of each model are analyzed from the aspects of the matching degree of the AI image and the prompt, the color composition and light composition of the image, and the general AI model that the generated AI image has an aesthetic sense is analyzed, and the designer does not need to take cumbersome steps. A satisfactory AI image can be obtained. The results show that Playground V2.5 model can be used as a general AI model, which has both aesthetic and design sense in various style design requirements. As a result, content designers can focus more on creative content development, and expect more groundbreaking technologies to merge generative AI with content design.