Seoha (Sara) Kim

Master's graduate focused on 4D Reconstruction and 3D Scene Understanding

kim-seoha@naver.com

About

I am a Master's graduate with a strong interest in 4D Reconstruction, 3D Scene Understanding, and Robotics.
My research focuses on developing intelligent systems capable of perceiving and interacting with dynamic 3D environments.

Coffee chats for research discussion are always welcome! ☕️

Publications

indicates equal contribution.

Per-Gaussian Embedding based Deformation for Deformable 3D Gaussian Splatting

Jeongmin Bae, Seoha Kim, Youngsik Yun, Hahyun Lee, Gun Bang, Youngjung Uh

ECCV 2024

Sync-NeRF: Generalizing Dynamic NeRFs to Unsynchronized Videos

Seoha Kim, Jeongmin Bae, Youngsik Yun, Hahyun Lee, Gun Bang, Youngjung Uh

AAAI 2024

Optimizing Dynamic NeRF and 3DGS with No Video Synchronization

Seoha Kim, Jeongmin Bae, Youngsik Yun, Hahyun Lee, Gun Bang, Youngjung Uh

ECCV 2024 Wild3D Workshop

Rethinking Open-Vocabulary Segmentation of Radiance Fields in 3D Space

Hyunjee Lee, Youngsik Yun, Jeongmin Bae, Seoha Kim, Youngjung Uh

Under Review

Vitae

  • ETRI 2023.01 - Present
    Academic-Research Cooperation
    Dynamic Scene Reconstruction Research
  • LG Display 2022.2 ‑ 2022.12
    Academic-Industrial Cooperation
    Knowledge Distillation Research
  • Yonsei University 2022 – 2024
    M.S. Student
    Artificial Intelligence
  • Plask 2021.3 – 2021.8
    AI Engineer
    3D Pose Estimation Research
  • Hyundai Mobis 2019.9 – 2020.2
    Data Scientist, Intern
    Internship in Data Science Team
  • Yonsei University 2015 - 2021
    B.A. Student
    Business Administration

Patents

KR 10-2024-0043684, Method and apparatus for Dynamic Gaussian Splatting using embedding-based deformation
KR 10-2023-0105173, Apparatus for representing dynamic neural radiance fields from unsynchronized videos
KR 10-2020-0022362, Apparatus of diagnosing noise quality of motor