Bio

I am Juil Koo, a second-year PhD student in the KAIST Visual AI Group, led by Prof. Minhyuk Sung. This summer, I joined Adobe Research as an intern, closely collaborating with Duygu Ceylan, Paul Guerrero and Chun-Hao Huang.

My research interests primarily revolve around stochastic differential equations and 3D geometry. Recently, I've been focusing on understanding and leveraging the rich prior of diffusion models to unlock their potential in diverse applications. Prior to this, I mainly worked on the intersection between 3D geometry and language. My research aims to address practical problems through theoretical insights.

My Erdős number is 3 (Juil Koo → Leonidas Guibas → Frances Yao → Paul Erdős).

"A painting of a boy using a laptop in front of a pond with water lilies, by Claude Monet", generated by DALL·E 2 and DALL·E 3.

News

Publications

SyncTweedies: A General Generative Framework Based on Synchronized Diffusions

Jaihoon Kim*, Juil Koo*, Kyeongmin Yeo*, Minhyuk Sung (* co-first author.)

NeurIPS 2024

Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses

Seungwoo Yoo, Juil Koo, Kyeongmin Yeo, Minhyuk Sung

NeurIPS 2024

[Paper]
Posterior Distillation Sampling

Juil Koo, Chanho Park, Minhyuk Sung

CVPR 2024

SALAD: Part-Level Latent Diffusion for 3D Shape Generation and Manipulation

Juil Koo*, Seungwoo Yoo*, Minh Hieu Nguyen*, Minhyuk Sung (* co-first author.)

ICCV 2023

PartGlot: Learning Shape Part Segmentation from Language Reference Games

Juil Koo, Ian Huang, Panos Achlioptas, Leonidas Guibas, Minhyuk Sung

CVPR 2022 (Oral)

[Project] [Paper] [Code] [Video]

Academic Service