I am a Ph.D. student in computer science highly interested in physically based rendering. Specifically, my research aims to accelerate physically based rendering methods via deep learning. Not limited to this, I m also interested in recent rendering techniques such as implicit neural representations and differentiable rendering, which I did some projects about these areas. I’m looking forward to the day when people can enjoy realistic rendering anytime and anywhere!
Research Interest
Ray Tracing, Physically Based Rendering, Neural Rendering
News
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Mar 2024 - Our work has been accepeted to CVPR 2024!!
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Aug 2023 - I’m pursuing Ph.D. in our SGVR Lab!
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Jul 2023 - I got a Best Master's Thesis Award from Korea Computer Graphics Society! Thank you for the honor!
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May 2023 - I just presented our work in I3D 2023, which is held in Unity Technology, Seattle! It was amazing to interact with graphics researchers worldwide!
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Sep 2022 - I gave a talk at the Korean domestic conference, KSC 2022. This talk is about optimizing neural networks and training schemes on a large GPU machine to accelerate training and testing.
Education
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PhD, Computer Science, KAIST (Aug 2023 ~ Present)
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GPA 4.22/4.3
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MS, Computer Sciene, KAIST (Aug 2021 ~ Aug 2023)
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GPA 4.2/4.3
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BS, Computer Science, Minor in Electrical Engineering, KAIST (Mar 2017 ~ Aug 2021)
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Cum Laude (GPA 3.80/4.3)
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Korea Science Academy of KAIST (Feb 2014 ~ Feb 2017)
Publications
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UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and UnFavOrable SEts
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User-Controlled Layout Editing with Neural Style Transfer
Proceedings of Korea Computer Grahpics Society Conference (KCGS) 2023
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Monte Carlo Image Denoising using Spatial Information of Light Bounces
Proceedings of Korea Information Science Society Conference (KCC) 2022
Invited Talks & Writings
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Pixel-wise Guidance for Utilizing Auxiliary Features in Monte Carlo Denoising
KCGS 2023
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Computer Graphics: Creating a New World Inside the Computer
KAIST magazine “Behind Science” 2023
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Accelerating Deep-Learning-Based Denoising Methods via High Performance Computing
GPU tutorial of KSC 2022
Experience
Scholarships and Awards
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Best Master's Thesis Award from Korea Computer Graphics Society (2023)
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Excellence Award as Teaching Assistant in School of Computing, KAIST (2022 Fall, 2022 Spring)
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Excellence Award in Undergraduate Research Program in KAIST (2021)
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Korea Presidential Science Scholarship ($10K per year) (2017~2020)
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SK Hynix Scholarship ($10K per year, guaranteed employment) (2019~)
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Korea National Representative of APAO (Asia-Pacific Astronomy Olympiad) (2013, 2015)
Won a Silver Medal in APAO 2013 Junior session
Teaching
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Teaching Assistant, Computer Graphics (CS500), Fall 2023
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Teaching Assistant, Data Structure (CS206), Spring 2023, Fall 2022, Spring 2022
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Teaching Assistant, Interactive Computer Graphics (CS482), Fall 2021
Projects
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Kernel Refinement for Monte Carlo Denoising using Pixel-wise Discriminator (2022)
Class Project (CS580)
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Voted as Best Project
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Refine denoising kernel based on pixel-wise scores of the U-Net discriminator
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Indoor Spatial Modeling and Rendering via Neural Rendering (2021)
Research Project
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Contribution of Auxiliary Features to Monte Carlo Denoisers Based on Deep Learning (2021)
Research Project (Excellence Award on Undergraduate Research Program in 2021)
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Analyzing & Enhancing contributions of auxiliary features (albedo, normal, and depth) by adding channel attention to existing denoisers
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Applied multi-task learning by adding auxiliary tasks of reconstructing auxiliary features from a denoised image to enhance the semantics of auxiliary features
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Scene Generator with Blender 2.93 (2021)
Research Project
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Generates scenes with various camera, material, and lighting settings by path-tracing using Cycles renderer supported by Blender
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Extracts geometric features (albedo, normal, depth) of each scene
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Current Monte-Carlo denoising methods involves deep learning which requires a lot of data. This scene generator is expected to make rich training dataset for this task easily.
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Simple Ray Tracer on CPU (2020)
Individual Project
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Re-implemented the ray tracer following the book series Ray Tracing in One Weekend
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Motion Detector for Interactive Online Real-time Class (2020)
Class Project (Introduction to AI CS470, A+)
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Detects simple hand gestures and alarms sudden movement for interactive online classes
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Contributing to preprocessing data and implementing an application using Openpose and Zoom SDK
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Mini-C Interpreter (2019)
Class Project (Compiler Design CS420)
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Implemented a mini-C interpreter with an error handler that handles common syntax errors
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Contributed to constructing syntax rules of mini-C and implementing lexer and parser
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MADMOVIE, a movie-critics website (2019)
Individual Project
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Implemented and managed server and database based on Node.js and PostgreSQL
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Crawled information and critics of currently screening movies using Beautiful Soup and Python
