AHCI RESEARCH GROUP

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OUR RESEARCH

Scientific Publications

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2025

Kim, M.; Kim, T.; Lee, K. -T.

3D Digital Human Generation from a Single Image Using Generative AI with Real-Time Motion Synchronization Journal Article

In: Electronics (Switzerland), vol. 14, no. 4, 2025, ISSN: 20799292 (ISSN).

Abstract | Links | BibTeX | Tags: 3D digital human, 3D human generation, digital twin, Generative AI, pose estimation, real-time motion synchronization, single image processing, SMPL-X, Unity 3D

@article{kim_3d_2025,

title = {3D Digital Human Generation from a Single Image Using Generative AI with Real-Time Motion Synchronization},

author = {M. Kim and T. Kim and K. -T. Lee},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218855876&doi=10.3390%2felectronics14040777&partnerID=40&md5=f1d0a0238c6422327901e4d4b6a43727},

doi = {10.3390/electronics14040777},

issn = {20799292 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Electronics (Switzerland)},

volume = {14},

number = {4},

abstract = {The generation of 3D digital humans has traditionally relied on multi-view imaging systems and large-scale datasets, posing challenges in cost, accessibility, and real-time applicability. To overcome these limitations, this study presents an efficient pipeline that constructs high-fidelity 3D digital humans from a single frontal image. By leveraging generative AI, the system synthesizes additional views and generates UV maps compatible with the SMPL-X model, ensuring anatomically accurate and photorealistic reconstructions. The generated 3D models are imported into Unity 3D, where they are rigged for real-time motion synchronization using BlazePose-based lightweight pose estimation. To further enhance motion realism, custom algorithms—including ground detection and rotation smoothing—are applied, improving movement stability and fluidity. The system was rigorously evaluated through both quantitative and qualitative analyses. Results show an average generation time of 211.1 s, segmentation accuracy of 92.1%, and real-time rendering at 64.4 FPS. In qualitative assessments, expert reviewers rated the system using the SUS usability framework and heuristic evaluation, confirming its usability and effectiveness. This method eliminates the need for multi-view cameras or depth sensors, significantly reducing the barrier to entry for real-time 3D avatar creation and interactive AI-driven applications. It has broad applications in virtual reality (VR), gaming, digital content creation, AI-driven simulation, digital twins, and telepresence systems. By introducing a scalable and accessible 3D modeling pipeline, this research lays the groundwork for future advancements in immersive and interactive environments. © 2025 by the authors.},

keywords = {3D digital human, 3D human generation, digital twin, Generative AI, pose estimation, real-time motion synchronization, single image processing, SMPL-X, Unity 3D},

pubstate = {published},

tppubtype = {article}

}