I am a master's student at Computer Vision Lab (advisor: Prof. Bohyung Han), Seoul National University (SNU). Recently, I worked with as a research intern at Computer Vision Lab advised by Prof. Bohyung Han. Before joining Computer Vision Lab, I was a research intern at T-Brain and a visiting student at CLVR Lab at the University of Southern California advised by Prof. Joseph Lim. I also spent great time with Prof. Byoung-Tak Zhang at BioIntelligence Lab, SNU before enrollment.
My research interests come from a question, "How people can learn from small amounts of data or coarse data such as noisy or weak-labeled data and why machine cannot?" My goal is applying cognitive science to machine learning vice versa to dig into this question. Meanwhile, I am also interested in machine learning approaches to solve this question. Shortly, I am interested in three fields as follows:
- Cognitive Science: Curiosity, Procedural Memory
- Computer Vision: Action Recognition/Localization, Weakly-supervised Instance Segmentation
- Reinforcement Learning: Exploration Strategies, Dynamics Randomization
- [09/2019] I joined Computer Vision Lab @ Seoul National University as a master's student advised by Professor Bohyung Han
- [10/2018] One paper "Robust harmonic field based tooth segmentation in real-life noisy scanned mesh" is accepted to SPIE Medical Imaging (@San Diego, Feb 2019)
- [09/2018] I joined Computer Vision Lab @ Seoul National University as a research intern advised by Professor Bohyung Han
- [05/2018] I joined T-Brain @ SKT, Seoul, Korea, as a research intern
- [02/2018] I joined CLVR @ University of Southern California as a visiting student advised by Professor Joseph Lim
Seoul National University
Seoul National University
(Summa Cum Laude)
(Apr 2015- Jan 2017 : Military Service)
Computer Vision Lab, Seoul National University
Research Intern, Advisor : Bohyung Han
Developed an end-to-end weakly-supervised instance segmentation framework via object detection.
CLVR Lab, University of Southern California
Visitng Student, Advisor : Joseph Lim
Developed a demonstration quality assement framework via Meta-Learning.
BioIntelligence Lab, Seoul National University
Research Intern, Advisor : Byoung-Tak Zhang
Developed a discourse system acting as a cashier using Hidden Markov Model.
T-Brain, SKT, Korea
Cybercrime Investigation Unit, Seoul Metropolitan Police Agency
Investigator (Auxiliary Police) - as a substitute of military service
Weakly Supervised Instance Segmentation by Community Learning
Jaedong Hwang*, Seohyun Kim*, Jeany Son, Bohyung Han.
arXiv. 2020. [arxiv].
Robust harmonic field based tooth segmentation in real-life noisy scanned mesh
Jaedong Hwang*, Sanghyeok Park*, Seokjin Lee*, Yeong-Gil Shin.
SPIE 10949, Medical Imaging 2019: Image Processing. [paper], [poster]
An adaptive computational discourse system based on data-driven learning algorithm
Seungwon Lee*, Jaedong Hwang*, Eunsol Kim, Byoung-Tak Zhang.
International Symposium on advanced Intelligent Systems (ISIS 2015) (Vol. 201). [paper]
Best Session Paper Awards
Best Paper of Brain-Mind-Behavior department2017
Seoul Metropolitan Police Agency Award Certificate2016
ISIS 2015 Best Session Paper Award2015
Seoam Scholarship Foundation (Merit-based)
Meta-Learned Suitability Assessor for Noisy Demonstration Sets
Advisor : Joseph Lim
Multi Label Generative Adversarial Network
Advisor : Byoung-Tak Zhang