Eun Woo Im [ɯnu ɪm] (임은우, 任殷佑)

Hello World! and welcome to my website.

I am a Computer Science Ph.D. student advised by Prof. Vivek Gupta at Arizona State University. My ultimate research goal is to construct a reliable multimodal AGI system and contribute to its practical and ethically proper deployment.

Prior to ASU, I obtained my M.S. in Artificial Intelligence (2023) and B.S. in Mathematics (2021) from Hanyang University in Seoul, Republic of Korea. During the period, I was fortunate to have supervision of Prof. Tae Hyun Kim on computational imaging tasks and Prof. Jae Hong Seo on machine learning applications and cryptology. In Fall 2020, I interned at KIST, where I developed microscopy imagery processors and classifier systems.

If you have any inquiries, please feel free to reach me out by email.

Email  /  GitHub  /  Google Scholar  /  LinkedIn  /  CV

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📰 News
  • 02/2026
    A new survey paper is released. Video Generation Models: A Survey of Post-Training and Alignment
  • 01/2026
    The following paper has been accepted to ICLR 2026. Self-Aug: Query and Entropy Adaptive Decoding for Large Vision-Language Models
  • 09/2025
    A new preprint is released. Self-Augmented Visual Contrastive Decoding
  • 08/2025
    A new preprint is released. Harnessing Meta-Learning for Controllable Full-Frame Video Stabilization
  • 02/2025
    The following paper has been accepted to CVPR 2025. VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models
  • 11/2024
    A new preprint is released. Evaluating Temporal Hallucinations in Multimodal Large Language Models
  • 04/2024
    I will be joining Arizona State University as a Ph.D. student.
  • 02/2024
    The following paper has been accepted to CVPR 2024. Harnessing Meta-Learning for Improving Full-Frame Video Stabilization
  • 08/2023
    I defended my thesis and received the Master's degree from Hanyang University. Thank you for your support.
  • 08/2023
    The following paper has been accepted to CIKM 2023. Deep Variational Bayesian Modeling of Haze Degradation Process
    (Long Paper, Oral Presentation)

📚 Selected Publication

* denotes equal contribution.

project image Video Generation Models: A Survey of Post-Training and Alignment
Chaoyu Li, Xiaoyi Gu, Yogesh Kulkarni, Eun Woo Im, Mohammadmahdi Honarmand, Zeyu Wang, Juntong Song, Fei Du, Xilin Jiang, Kexin Zheng, Tianzhi Li, Fei Tao, Pooyan Fazli.
TechRxiv / project page
project image Self-Aug: Query and Entropy Adaptive Decoding for Large Vision-Language Models
Eun Woo Im, Muhammad Kashif Ali, Vivek Gupta
ICLR 2026 / arXiv / code / project page
project image Harnessing Meta-Learning for Controllable Full-Frame Video Stabilization
Muhammad Kashif Ali, Eun Woo Im, Dongjin Kim, Tae Hyun Kim, Vivek Gupta, Haonan Luo, Tianrui Li
arXiv / code
project image VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models for Video Understanding
Chaoyu Li, Eun Woo Im, Pooyan Fazli
CVPR 2025 / arXiv / code / project page
project image Harnessing Meta-Learning for Improving Full-Frame Video Stabilization
Muhammad Kashif Ali, Eun Woo Im, Dongjin Kim, Tae Hyun Kim
CVPR 2024 / arXiv / code
project image Deep Variational Bayesian Modeling of Haze Degradation Process
Eun Woo Im*, Junsung Shin*, Sungyong Baik, Tae Hyun Kim
CIKM 2023 / arXiv / code

❝ Favorite Quotes
  • The biggest risk is not taking any risk. In a world that changing really quickly, the only strategy that is guaranteed to fail is not taking risks.
    - Mark Elliot Zuckerberg
  • Never let go of your appetite to go after new ideas, new experiences, and new adventures.
    - Steven Paul Jobs
  • Be humble in your confidence yet courageous in your character.
    - Kun-Hee Lee