Huiwon Jang
Graduate student at KAIST
KAIST AI
huiwoen0516 [AT] kaist.ac.kr
About
I am a PhD student at Korea Advanced Institute of Science and Technology (KAIST), advised by Prof. Jinwoo Shin. Prior to this, I received B.S. in Mathematical Science and Computer Science at KAIST in 2023. My research mainly focuses on visual representation learning, which enables models to perceive visual content and ultimately understand the world. In particular, my recent research interest focuses on self-supervised learning and visual tokenization for visual generation and understanding.
Publications
Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction
Huiwon Jang, Sihyun Yu, Jinwoo Shin, Pieter Abbeel, Younggyo Seo
CVPR 2025
Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think
Sihyun Yu, Sangkyung Kwak, Huiwon Jang, Jongheon Jeong, Jonathan Huang, Jinwoo Shin, Saining Xie
ICLR 2025, Oral Presentation (207/11672=1.77%)
TrackIME: Enhanced Video Point Tracking via Instance Motion Estimation
Seong Hyeon Park, Huiwon Jang, Byungwoo Jeon, Sukmin Yun, Paul Hongsuck Seo, Jinwoo Shin
NeurIPS 2024, Spotlight Presentation (326/15671=2%)
Adversarial Robustification via Text-to-Image Diffusion Models
Daewon Choi*, Jongheon Jeong*, Huiwon Jang, Jinwoo Shin
ECCV 2024, Oral Presentation (200/8585=2.3%)
Visual Representation Learning with Stochastic Frame Prediction
Huiwon Jang, Dongyoung Kim, Junsu Kim, Jinwoo Shin, Pieter Abbeel, Younggyo Seo
ICML 2024
Modality-agnostic Self-supervised Learning with Meta-learned Masked Auto-encoder
Huiwon Jang*, Jihoon Tack*, Daewon Choi, Jongheon Jeong, Jinwoo Shin
NeurIPS 2023
Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
Huiwon Jang*, Hankook Lee*, Jinwoo Shin
ICLR 2023, Spotlight Presentation (280/4956=5.6%)
NeurIPSW-MetaLearn 2022
Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction
Huiwon Jang, Sihyun Yu, Jinwoo Shin, Pieter Abbeel, Younggyo Seo
CVPR 2025
Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think
Sihyun Yu, Sangkyung Kwak, Huiwon Jang, Jongheon Jeong, Jonathan Huang, Jinwoo Shin, Saining Xie
ICLR 2025, Oral Presentation (207/11672=1.77%)
TrackIME: Enhanced Video Point Tracking via Instance Motion Estimation
Seong Hyeon Park, Huiwon Jang, Byungwoo Jeon, Sukmin Yun, Paul Hongsuck Seo, Jinwoo Shin
NeurIPS 2024, Spotlight Presentation (326/15671=2%)
Adversarial Robustification via Text-to-Image Diffusion Models
Daewon Choi*, Jongheon Jeong*, Huiwon Jang, Jinwoo Shin
ECCV 2024, Oral Presentation (200/8585=2.3%)
Visual Representation Learning with Stochastic Frame Prediction
Huiwon Jang, Dongyoung Kim, Junsu Kim, Jinwoo Shin, Pieter Abbeel, Younggyo Seo
ICML 2024
Modality-agnostic Self-supervised Learning with Meta-learned Masked Auto-encoder
Huiwon Jang*, Jihoon Tack*, Daewon Choi, Jongheon Jeong, Jinwoo Shin
NeurIPS 2023
Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
Huiwon Jang*, Hankook Lee*, Jinwoo Shin
ICLR 2023, Spotlight Presentation (280/4956=5.6%)
NeurIPSW-MetaLearn 2022
AltUB: Alternating Training Method to Update Base Distribution of Normalizing Flow for Anomaly Detection
Yeongmin Kim*, Huiwon Jang*, Dongkeon Lee, Hojin Choi
Arxiv preprint, 2022
Education
Korea Advanced Institute of Science and Technology (KAIST)Mar. 2023 - Present
PhD. Student in Artificial Intelligence
Korea Advanced Institute of Science and Technology (KAIST)Mar. 2019 - Feb. 2023
B.S. in Mathematical Science and Computer Science
Experience
AI Research InternOct. 2022 - Oct. 2023
i-SENSAcademic Services
Conference Reviewer, IJCAI'23; NeurIPS'24-25; ICLR'25; ICML'25; CVPR'25; ICCV'25; AISTATS'25
Journal Reviewer, IJCV
Honors & Awards
Travel Award, International Conference on Machine Learning (ICML) 2024Jul. 2024
Travel Award, Conference on Neural Information Processing Systems (NeurIPS) 2023 Dec. 2023
Travel Award, International Conference on Learning Representations (ICLR) 2023 May. 2023
Recipient, Google Conference Scholarships (APAC)May. 2023
Invited Talks
Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder
Samsung Electronics Device Solution (DS)Oct. 2024
Samsung AI Forum (SAIF) 2023Nov. 2023
Samsung Advanced Institue of Technology (SAIT)Jun. 2023
Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
International Conference on Learning Representations (ICLR)May. 2023