이진준 교수
Jin-Jun Lee
KAIST 문화기술대학원 · 신경과학
연구실 소개
이진준 교수의 연구실은 인터랙티브 미디어 아트와 인공지능 기반 예술의 융합을 중심으로, 다감각 경험을 구현하는 기술적 혁신과 함께, 사회적 소외된 집단의 목소리를 예술적으로 재현하는 데 초점을 맞추고 있습니다. 특히 투명한 프로젝션 매핑 기반 상호작용 시스템, AI 기반 객체 탐지 및 사운드화 기법, 그리고 전통 문화적 정서를 디지털 미디어로 재해석하는 다중모odal 전환 프레임워크를 개발하고 있습니다. 연구는 기술적 구현뿐 아니라, 예술이 지닌 사회적 맥락과 정체성의 복합성을 탐구하는 데에도 기여하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
5As interactive media arts evolve, there is a growing demand for technologies that offer multisensory experiences beyond audiovisual elements in large-scale projection mapping exhibitions. However, traditional methods of providing tactile feedback are impractical in expansive settings due to their bulk and complexity. The EMPop system is the proposed solution, utilizing a straightforward design of electromagnets and permanent magnets making projection mapping more interactive and engaging. Our sy
Abstract The authors present gOd, mOther and sOldier—Nowhere in Somewhere Series 2022, a work that was conceptualized and created by artist Jinjoon Lee and his TX Creative Media Lab at KAIST, realized through the remote cooperation of eight local collaborators across Southeast Asia. The authors used artificial intelligence–based object detectors and sonification techniques in a work of media art to symbolize the voicelessness of those at the margins of society in Southeast Asia. These algorithms
We introduce an efficient algorithm for general data mosaicing, based on the simulation-based inference paradigm. Our algorithm takes as input a target datum, source data, and partitions of the target and source data into fragments, learning distributions over averages of fragments of the source data such that samples from those distributions approximate fragments of the target datum. We utilize a model that can be trivially parallelized in conjunction with the latest advances in efficient simul
This paper examines diffused multiplicity as an emergent characteristic of AI art, analyzing how multiple temporal, cultural, and aesthetic layers are embedded within these computational systems. Unlike traditional artistic production that maintains coherent aesthetic identities, AI artworks function as palimpsestic objects that contain multiple potential interpretations simultaneously. Through analysis of neural networks as synthetic media and examination of related artworks, this paper demonst
Abstract This paper analyzes the integration of East Asian literati traditions with contemporary multimedia through two artworks. It proposes a multimodal transcoding framework converting video frames into multisensory outputs via data-driven visualization and sonification. Using a modified turntable, the system interprets an artificial marble disc, created from the artist’s daily creation, to depict mental space using sumi ink. This aligns with literati traditions of expressing inner worlds thr
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