News
- Jun 2026 InverseCrafter is accepted to ECCV 2026.
- May 2026 AGSM is accepted to ICML 2026 Spotlight (top 2.2%).
- Feb 2026 FlowAlign is accepted to ICLR 2026.
- Dec 2025 Started Visiting Student (Remote) @ ETH Zürich.
Education
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KAIST –
M.S. in Artificial Intelligence
Advisor: Prof. Jong Chul Ye
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B.S. in Mathematics & Artificial Intelligence
Publications
2026
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arXiv preprintGeoFix: Geometry Fixing for 4D Consistent Generation Project Page
GeoFix aligns videos for geometric consistency and visual quality in 4D generation using a single depth consistency reward calibrated for camera overlap, both during training and inference-time alignment.
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ECCV 2026InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem
InverseCrafter is an inpainting inverse solver that reformulates novel view video generation as an inpainting problem solved in the latent space.
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ICML 2026 Spotlight (536/6352=2.2%)Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models Project Page
AGSM improves text–image alignment using score-level preference optimization with a Plackett–Luce objective without an explicit reward. By explicitly guiding positive and negative pairs within the diffusion score-matching loss, AGSM reduces SoftREPA’s failure modes while improving generation and editing across different backbones.
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ICLR 2026FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing Code
FlowAlign is an inversion-free, flow-based image editing method that achieves smooth and stable trajectories through a flow-matching loss. It also enables reversible editing by leveraging the intrinsic properties of ODE-based transformations.
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WACV 2026DreamMakeup: Face Makeup Customization using Latent Diffusion Models
DreamMakeup is a face makeup customization method that can get various conditioning as input - reference images, RGB colors, textual descriptions.
2024
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ACM MM 2024GaussianTalker: Real-Time High-Fidelity Talking Head Synthesis with Audio-Driven 3D Gaussian Splatting Code
GaussianTalker is a framework for real-time generation of pose-controllable talking heads. It leverages the fast rendering capabilities of 3D Gaussian Splatting (3DGS) while addressing the challenges of directly controlling 3DGS with speech audio.
Experience
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Visiting Student (Remote)
Advisors: Prof. Konrad Schindler, Dr. Dominik Narnhofer
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Undergraduate Research Intern
Advisor: Prof. Seungryong Kim