Jiin Im

Jiin Im

Research Assistant @ Spatial AI Lab, Hanyang University

About

I am a Research Assistant (previously Master's student) at the Spatial AI Lab, Hanyang University, advised by Prof. Je Hyeong Hong. My research interests lie in computer vision and computer graphics, with a focus on correspondence and spatial reasoning.

I am particularly interested in how correspondence can serve as a foundation for spatial reasoning, where the goal is to discover meaningful part-level relationships across objects, views, and modalities. My interests span both image-level and shape-level correspondence, including spectral approaches to matching across 3D geometries, and how these can be connected so that agents reason over spatial structure in a viewpoint-invariant manner.

This direction is motivated by real-world perception problems where appearance alone is insufficient: recognizing that two visually different objects share the same functional part, or generalizing manipulation skills across unseen environments. I believe spatial understanding grounded in correspondence is a key building block for such capabilities.

I am actively seeking Ph.D. opportunities starting in Fall 2027. If you are interested in discussing my research or potential collaborations, I'd love to grab a coffee at CVPR 2026 in Denver or chat over email! ☕

Education

Hanyang University Mar. 2026 - Present

Research Assistant (Advisor: Je Hyeong Hong)

Hanyang University Mar. 2024 - Feb. 2026

M.S. in Electronic Engineering (Advisor: Je Hyeong Hong)

Hanyang University Mar. 2020 - Feb. 2024

B.S. in Electronic Engineering, Summa Cum Laude

Publications

Chebyshev Differential Flows Teaser Image

Chebyshev Differential Flows for Shape Matching and Interpolation

Jiin Im, Sisung Liu, Je Hyeong Hong

Under review

Shape-of-You Teaser Image

Shape-of-You: Fused Gromov-Wasserstein Optimal Transport for Semantic Correspondence in-the-Wild

Jiin Im, Sisung Liu, Je Hyeong Hong

CVPR 2026

Paper Code
FUN-AD Teaser Image

FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training Data

Jiin Im*, Yongho Son*, Je Hyeong Hong

WACV 2025

Paper Code

Projects

Semantic Correspondence via Structural Information on 2D and 3D Domains Mar. 2025 - Present

Establishing semantic correspondence on both 2D image and 3D geometry domains using structural information, which is related to Shape-of-You.

Non-Rigid Registration of Deformed Point Clouds via Geometric Correspondence Jun. 2025 - Dec. 2025

Focused on estimating geometric correspondence in deformed point clouds to perform robust non-rigid registration.

Privacy-Preserving Geometric Description against Image Reconstruction Jun. 2024 - Feb. 2025

Explored geometric description methods that prevent original image recovery from descriptors while maintaining matching performance.

Unsupervised Anomaly Detection with Noisy Training Data Jan. 2023 - May. 2024

Addressing anomaly detection in unsupervised settings with noisy training data related to FUN-AD.

Academic Service

Experience

Hobbies

In my free time, I enjoy:

Contact

✉️ Email: skqldit33@hanyang.ac.kr

📍 Location: Engineering Center Annex Unit 415-1, Hanyang University, Seongdong-gu, Wangsimni-ro 222, Seoul, South Korea