I am currently a Postdoctoral Research Associate at Multimodal AI Lab at KAIST with Prof. Joon Son Chung. I received my PhD degree at the Electrical Engineering department at KAIST and was advised by Prof. In So Kweon. I earned my B.S. in Electrical Engineering from Georgia Institute of Technology in 2018. My current research interests lie in the general areas of computer vision and deep learning with a particular focus on:
chojw [at] kaist.ac.kr
Bldg N1, Rm 211, 291 Daehak-ro, Yuseong-gu, Daejeon, Korea, 34141
Ph.D. in Electrical Engineering
Aug 2018 - Aug 2023
KAIST, South Korea
Advisor: Prof. In So Kweon
B.S. in Electrical Engineering
Aug 2014 - May 2018
Georgia Institute of Technology, USA
Empirical study on using Adapters for debiased Visual Question Answering
Computer Vision and Image Understanding (CVIU), 2023 (Impact Factor 4.5)
[ Paper ]
Generative Bias for Robust Visual Question Answering
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Received Bronze Prize, 28th Samsung Humantech Paper Awards (Top 2.8%)
Excellent Paper Award IW-FCV
Also presented at "Workshop on Open-Domain Reasoning Under Multi-Modal Settings" in conjunction with CVPR 2023
MCDAL: Maximum Classifier Discrepancy for Active Learning
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2022 (Impact Factor 14.255)
[ Paper ]
Also presented at "The Workshop on Fine-Grained Visual Categorization" in conjunction with CVPR 2022
Investigating Top-k White-box and Transferable Black-box Attack
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2022
[ Paper ]
Single-Modal Entropy based Active Learning for Visual Question Answering
British Machine Vision Conference (BMVC), 2021
[ Paper ]
LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
IEEE International Conference on Computer Vision (ICCV), 2021 [Oral] (acceptance rate 3%)
[ Paper ]
Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillation
CVPR Multimodal Learning and Applications Workshop (CVPRW), 2021
[ Paper ]
Also presented at "Visual Question Answering Workshop" and "VizWiz Grand Challenge Workshop" in conjunction with CVPR 2021.