Keynote Speakers of CGIP 2024



Prof. Kazunori Miyata
Japan Advanced Institute of Science and Technology (JAIST), Japan

Prof. Kazunori Miyata received his B.S. in Applied Physics from Tohoku University in 1984 and his Master of Engineering and Doctor of Engineering from Tokyo Institute of Technology in 1986 and 1997, respectively. He has been a professor at Japan Advanced Institute of Science and Technology (JAIST) since 2002. In 1986, he became a researcher at the Tokyo Research Laboratory of IBM Japan, and in 1998 he was an assistant professor at the Faculty of Arts, Tokyo Polytechnic University. Since 2021, he is an academic staff under the joint appointment academic scheme at Universiti Utara Malaysia School of Creative Industry Management & Performing Arts. He is a fellow of The Institute of Image Electronics Engineers of Japan. His research mainly focuses on computer graphics, human computer interaction, fun computing, XR, and multimedia applications. He is a past president of the Japan Society for Art Science and Technology. He is a member of The Virtual Reality Society of Japan, Information Processing Society of Japan, Japan Society of Art Science and Technology, ACM, and IEEE.

Speech Title: "Computer Graphics as a Tool to Support Creative Activity"

Abstract: Thanks to the benefits of deep learning technologies, it is now possible to create highly accurate visual digital content with little effort. This technology, generative AI, is expected to drastically reduce our intellectual workload and dramatically change the social structure. On the other hand, CG technology is also a core technology that has already penetrated deeply into our daily lives. However, it is clear that the technical hurdles and workloads, such as the modeling capability of a target object, are high to realize one's idea as a CG image. In response to this challenge, a method called procedural technology is useful as a tool to streamline production work, i.e. a rapid prototyping tool, because it can instantly generate the desired content simply by changing parameters. In general, the design process includes reflection on the outputs. Designers improve their work through introspection and quiet thinking while working. Is it really possible for current generative AI to encourage such introspection? This talk will position CG as a tool to support creative activities and describe a framework for mining users' creativity through several examples. It will also show the potential for sharing content design ideas with others and for inheriting the design process.