Moon Ye-Bin
I am a Ph.D. student in Algorithmic Machine Intelligent (AMI) Lab, Dept. of Electronic Engineering, POSTECH, South Korea, advised by Prof. Tae-Hyun Oh. I finished my master's degree from AMILab in POSTECH, and bachelor's degree from Dept. Electrical and Electronic Engineering at Chung-Ang University (CAU), South Korea.
I am interested in data-centric model training and evaluation, especially within vision and language multi-modal characteristics.
Keywords: multi-modal learning, large vision-language models (LVLMs), large language models (LLMs), but not limited to
Contact: ybmoon[at]postech[dot]ac[dot]kr | aileenmoon96[at]gmail[dot]com
Information: CV, GitHub, Google Scholar
Publications
BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-language Models, Submitted
Moon Ye-Bin*, Nam Hyeon-Woo*, Wonseok Choi, Tae-Hyun Oh
Moon Ye-Bin*, Nam Hyeon-Woo*, Wonseok Choi, Tae-Hyun Oh
VLM’s Eye Examination: Instruct and Inspect Visual Competency of Vision Language Model, Submitted
Nam Hyeon-Woo*, Moon Ye-Bin*, Wonseok Choi, Lee Hyun, Tae-Hyun Oh
Nam Hyeon-Woo*, Moon Ye-Bin*, Wonseok Choi, Lee Hyun, Tae-Hyun Oh
SYNAuG: Exploiting Synthetic Data for Data Imbalance Problems, ICCV '23 Workshop
Moon Ye-Bin*, Nam Hyeon-Woo*, Wonseok Choi, Nayeong Kim, Suha Kwak, Tae-Hyun Oh
[arXiv]
Moon Ye-Bin*, Nam Hyeon-Woo*, Wonseok Choi, Nayeong Kim, Suha Kwak, Tae-Hyun Oh
[arXiv]
Propose to utilize synthetic data to address three distinctive data imbalance problems
[Workshop] ICCVw 2023 (MMFM: What is Next in Multimodal Foundation Models?)
TextManiA: Enriching Visual Feature by Text-driven Manifold Augmentation, ICCV'23
Moon Ye-Bin, Jisoo Kim, Hongyeob Kim, Kilho Son, Tae-Hyun Oh
[Project Page][Paper][arXiv]
Moon Ye-Bin, Jisoo Kim, Hongyeob Kim, Kilho Son, Tae-Hyun Oh
[Project Page][Paper][arXiv]
Propose a text-driven manifold augmentation method that semantically enriches visual feature spaces, regardless of data distribution
[Workshop] CVPRw 2023 (WFM: Workshop on Foundation Models)
[Workshop] ICCVw 2023 (MMFM: What is Next in Multimodal Foundation Models?)
Proposed ENInst with sub-task enhancement methods: instance-wise refinement for enhancing pixel localization quality and novel classifier composition for improving classification accuracy, based on the performance bottleneck analyses
[Conference] IPIU 2022, Best Paper Award
HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields, ECCV'22
Kim Jun-Seong*, Kim Yu-Ji*, Moon Ye-Bin, Tae-Hyun Oh
[Project Page][Paper][arXiv]
Kim Jun-Seong*, Kim Yu-Ji*, Moon Ye-Bin, Tae-Hyun Oh
[Project Page][Paper][arXiv]
Propose High Dynamic Range Plenoxels (HDR-Plenoxels) that learns the plenoptic function of the 3D scene from a comprehensive understanding of 3D information, physical radiance field, and varying camera settings inherent in 2D low dynamic range (LDR) images
[Workshop] CVPRw 2023 (3DMV: Learning 3D with Multi-View Supervision)
PROJECTS
Abnormal and Danger Signs Detection with LLMs, KRIT, 2023
Video Panoptic Segmentation and Depth Estimation, ETRI, 2022
Data Augmentation for Domain Adaptive Object Detection, LG Display, 2022
Weakly-supervised Low-shot Instance Segmentation, ETRI, 2021
Self-supervised Few-shot Learning by Episodic Instance Discrimination, ETRI, 2020
EDUCATION
Ph.D. in Electrical Engineering, POSTECH, Pohang, South Korea (current)
Mar.2022 -
Master in Electrical Engineering, POSTECH, Pohang, South Korea
Sports AIX Program
Mar. 2020 –Feb. 2022
Bachelor in Electrical and Electronic Engineering, Chung-Ang University, Seoul, South Korea
Magna cum laude
Mar. 2016 – Feb. 2020
EXTRA
Conference Reviewer
ACCV'24, ECCV'24, CVPR'24
ICCV'23, CVPR'23, WACV'23
Teaching Experiences
[NAVER Boostcamp AI Tech 6th] Data-centric CV course, NAVER & Upstage, 2023
[EECE236] Learning Electronic Engineering with MATLAB, POSTECH, 2020
Deep Learning Seminar
POSTECH AMILab seminar [YouTube]
POSTECH EE-group deep learning seminar
POSTECH PAIR (CVLab, CGLab, MLLab, AMILab) seminar