Jaeyoung Chung

I am a Ph.D student in the Computer Vision Lab at Seoul National University (SNU), advised by Kyoung Mu Lee. My research focuses on 3D vision, particularly 3D reconstruction and generation. I have served as a reviewer for CVPR, ECCV, AAAI, and TPAMI. I interned at the Intelligent Multimedia Group within Microsoft Research Asia during the winter of 2021.

During my undergraduate studies, I majored in Electrical and Computer Engineering at the same university and participated in various projects, such as developing embedded systems on robots and sounding rockets (detailed in the Team Project and Mini Project section). In my master course, I focused on research in visual-inertial odometry, leveraging inertial measurement units (IMUs).

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We propose a method to construct a holistic 3D Gaussian splatting scene using a feed-forward network by taming the pretrained network to align with the Yin-Yang grid.

We introduce a method to optimize Gaussian splatting with 360 panorama images, considering omnidirectional camera model.

We developed a 3D Gaussian splatting scene generation pipeline that iteratively generates and aligns parts of the scene.

We introduce a method to optimize Gaussian splatting with a limited image set, mitigating overfitting by incorporating a estimated depth map as a geometric guide.

We study the incremental learning scenario in Neural Radiance Fields (NeRF) first time and propose a self-distillation-based method alleviating catastrophic forgetting without memory increasing.

We propose a constrained implicit algebraic surface as the primitive with few learnable coefficients and higher geometrical complexities.

We propose a precise navigation system using wheel odometry, Low-Grade inertial measurement unit, and monocular camera in Urban Area. VIO Simluation code (Pended)

We develop whole solid sounding rockets from engine, fuel, body, electric system including wing control, parachute control, ignition control, data(pressure, accel, rotation) measurement, and communication system.

I was a leader of electric system team. (2016 ~ 2017)

We develop the whole system of quadcopter drone from scratch and try to control some complex movement by utilizing reinforcement learning.

We develop an electronic bicycle with an interchangeable front wheel between motor-powered wheel and normal. We design the motor control system deliberately for similar user experiences with pedal assistance system (PAS).

I mainly develop embedded system and algorithm including power, circuit, PID control, etc.

I made this tree out of discarded materials including green pcb-boards (as leaf), shiny light LED arrays, a drone that reacts when approached, and a blower that floats a ping-pong ball

Best Paper Runner-up Awards at the CVPR 2024 Workshop for Learning 3D with Multi-View Supervision (2024)

Excellence Prize at 35th Workshop on Image Processing and Image Understanding (2023)

“Stars of Tomorrow” Award in Microsoft Research Asia Internship (2022)

Second Prize at HuggingFace Flax/JAX community week (2021)

Gold Prize at 33th Workshop on Image Processing and Image Understanding (2021)

First Prize at Dongbu Award for SNU Creative Design Fair (2015)

Taught high school students embedded system at Doseon high school (Oct. - Nov. 2020)

Taught freshman embedded system design (Mar. - Jun. 2016)

Taught high school students Arduino at Gwangyang Jecheol high school (Jan. - Feb. 2015)

I borrow this format from Ben Mildenhall website.