• Title/Summary/Keyword: Generative AI video production

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Analysis of the possibility of utilizing customized video production using generative AI

  • Hyun Kyung Seo
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.11
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    • pp.127-136
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    • 2024
  • As generative AI technology develops, the paradigm of video production is also changing. After going through an initial stage where it could not be used as actual video footage due to low quality and difficulties with consistency and continuity, various videos produced with generative AI are being used in the video industry. Following these changes, this paper identifies the potential of customized generative AI. It examines the direction of technological development of generative AI in the video industry and analyzes recent cases in advertising, film, and animation to reveal that the reason for the increased utilization of generative AI is to achieve the essential purpose of content as well as quality results. Through this process, we expect the potential of generative AI in the video industry.

Transforming Text into Video: A Proposed Methodology for Video Production Using the VQGAN-CLIP Image Generative AI Model

  • SukChang Lee
    • International Journal of Advanced Culture Technology
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    • v.11 no.3
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    • pp.225-230
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    • 2023
  • With the development of AI technology, there is a growing discussion about Text-to-Image Generative AI. We presented a Generative AI video production method and delineated a methodology for the production of personalized AI-generated videos with the objective of broadening the landscape of the video domain. And we meticulously examined the procedural steps involved in AI-driven video production and directly implemented a video creation approach utilizing the VQGAN-CLIP model. The outcomes produced by the VQGAN-CLIP model exhibited a relatively moderate resolution and frame rate, and predominantly manifested as abstract images. Such characteristics indicated potential applicability in OTT-based video content or the realm of visual arts. It is anticipated that AI-driven video production techniques will see heightened utilization in forthcoming endeavors.

Utilization Strategies of Generative AI Platforms for CG Education (CG 교육을 위한 생성형 인공지능 플랫폼 활용 방안)

  • Donghee Suh
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.357-364
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    • 2023
  • Due to the rapid advancement of AI technology, generative artificial intelligence platforms are experiencing innovative applications in various fields. In this paper, it examines research cases involving the utilization of AI in education, explore instances where generative AI platforms are applied in the realm of creative endeavors, and discuss the direction of utilizing generative AI in educational contexts. In the field of computer graphics, this study introduced generative AI platforms that are applicable for image creation, editing, and video editing. It also proposed platforms that can be utilized in the video editing production process. These generative AI platforms not only offer advantages in terms of efficiency, by reducing the efforts of creators and saving time in the production process, but they also present positive aspects in enhancing individual capabilities. It is advocated that their swift integration into education is necessary, considering these benefits. This study aims to provide direction for the expansion of creative education utilizing generative AI platforms.

Prospects and Issues on the Expansion of AI Tech's Influence in Film Creation (AI 기술의 영상제작 분야 영향력 확대에 관한 전망과 쟁점)

  • Hanjin Lee;Minhee Kim;Juwon Yun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.4
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    • pp.107-112
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    • 2024
  • One More Pumpkin won the grand prize at the 2023 Dubai International AI Film Festival, and new possibilities were also opened through the International AI and Metaverse Film Festival (GAMFF), which was held for the first time in Korea. Generative works began to stand out in earnest, with 527 diverse works from 42 countries at home and abroad using AI and metaverse technology submitted to this contest. AI is being used in a variety of fields, including the creation and implementation of digital characters through combination with VFX, improving the efficiency of video production, and managing the overall video production process. This contributes to saving human and material resources required for production and significantly improving the quality of produced videos. However, generative AI also has ambiguity in copyright attribution, ethical issues inherent in the learned dataset, and technical limitations that fall short of the level of human emotion and creativity. Accordingly, this study suggests implications at the level of production, screening, and use, as generative AI may have an impact in more areas in the future.

A Study on the Utilization of Generative AI for Employment Portfolio Creation (취업 포트폴리오 제작을 위한 생성형 AI 활용 연구)

  • Kim Sungrim;Kwon Joonhee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.3
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    • pp.1-12
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    • 2024
  • This study explores how generative AI technology can be utilized to create more efficient and effective employment portfolios in the rapidly changing job market and recruitment landscape. To achieve this, the study first conducted an in-depth analysis of recent employment trends and recruitment patterns, categorizing various generative AI tools based on their application in areas such as resume writing, portfolio design, and video production. Particularly, this research includes a case study of a career planning course in a university setting, where generative AI was applied, to empirically evaluate its potential for educational use. Through this case study, the research thoroughly examines how generative AI can contribute to efficient job preparation and skill enhancement for job seekers. The findings suggest that generative AI plays a critical role in providing personalized information, generating creative ideas, and enhancing both the visual and functional quality of employment portfolios, ultimately contributing to increased competitiveness in the job market. The study also emphasizes the need for further research on the expanding scope and effectiveness of generative AI as the technology continues to evolve.

A study of virtual human production methods: Focusing on video contents

  • Kim, Kwang Jib
    • International journal of advanced smart convergence
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    • v.13 no.1
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    • pp.23-36
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    • 2024
  • Interest in virtual humans continues to increase due to the development of generative AI, extended reality, computer graphics technology, and the spread of a converged metaverse that goes beyond the boundaries between reality and virtuality. Despite the negative public opinion that virtual humans were just temporary form of entertainment event in the early days of their emergence, the reason they are showing continuous growth is due to the unique characteristics of virtual humans and the expansion of diverse usage from technological advancements. The production of video content using virtual humans is becoming vigorously active, but currently there is limitation and no exact process for the technology to apply virtual humans to video content for it to be produced accordingly to the characteristics or situations of virtual humans. In this study, we investigated the characteristics of virtual human production technology methods & processes, and identifying the impact of each production technology on the production environment through examples of virtual human content applied to domestic and international video contents. In conclusion, by proposing an appropriate production method for each content, we hope to develop and assist production practitioners so they can effectively use virtual humans in video content production.

Comparison of online video(OTT) content production technology based on artificial intelligence customized recommendation service (인공지능 맞춤 추천서비스 기반 온라인 동영상(OTT) 콘텐츠 제작 기술 비교)

  • CHUN, Sanghun;SHIN, Seoung-Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.99-105
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    • 2021
  • In addition to the OTT video production service represented by Nexflix and YouTube, a personalized recommendation system for content with artificial intelligence has become common. YouTube's personalized recommendation service system consists of two neural networks, one neural network consisting of a recommendation candidate generation model and the other consisting of a ranking network. Netflix's video recommendation system consists of two data classification systems, divided into content-based filtering and collaborative filtering. As the online platform-led content production is activated by the Corona Pandemic, the field of virtual influencers using artificial intelligence is emerging. Virtual influencers are produced with GAN (Generative Adversarial Networks) artificial intelligence, and are unsupervised learning algorithms in which two opposing systems compete with each other. This study also researched the possibility of developing AI platform based on individual recommendation and virtual influencer (metabus) as a core content of OTT in the future.

3D Object Extraction Mechanism from Informal Natural Language Based Requirement Specifications (비정형 자연어 요구사항으로부터 3D 객체 추출 메커니즘)

  • Hyuntae Kim;Janghwan Kim;Jihoon Kong;Kidu Kim;R. Young Chul Kim
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.9
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    • pp.453-459
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    • 2024
  • Recent advances in generative AI technologies using natural language processing have critically impacted text, image, and video production. Despite these innovations, we still need to improve the consistency and reusability of AI-generated outputs. These issues are critical in cartoon creation, where the inability to consistently replicate characters and specific objects can degrade the work's quality. We propose an integrated adaption of language analysis-based requirement engineering and cartoon engineering to solve this. The proposed method applies the linguistic frameworks of Chomsky and Fillmore to analyze natural language and utilizes UML sequence models for generating consistent 3D representations of object interactions. It systematically interprets the creator's intentions from textual inputs, ensuring that each character or object, once conceptualized, is accurately replicated across various panels and episodes to preserve visual and contextual integrity. This technique enhances the accuracy and consistency of character portrayals in animated contexts, aligning closely with the initial specifications. Consequently, this method holds potential applicability in other domains requiring the translation of complex textual descriptions into visual representations.