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About

AI Researcher at LG Electronics, M.S. in Computer Science at Korea University. Interested in computer vision, especially in diffusion generative models and its controllable generation.

For more information, please refer to my CV

Publications

Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters

Gyuseong Lee*, Wooseok Jang*, Jin Hyeon Kim, Jaewoo Jung, Seungryong Kim

WACV 2025 (To be presented), Oct. 2023

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DiffMatch: Diffusion Model for Dense Matching

Jisu Nam, Gyuseong Lee, Sunwoo Kim, Hyeonsu Kim, Hyoungwon Cho, Seyeon Kim, Seungryong Kim

ICLR 2024 Oral Presentation, May 2024

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Improving Sample Quality of Diffusion Models Using Self-Attention Guidance

Susung Hong, Gyuseong Lee, Wooseok Jang, Seungryong Kim

ICCV 2023, Oct. 2023

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Depth-Aware Guidance with Self-Estimated Depth Representations of Diffusion Models

Gyeongnyeon Kim*, Wooseok Jang*, Gyuseong Lee*, Susung Hong, Junyoung Seo, Seungryong Kim

Pattern Recognition, Apr. 2024

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MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation

Junyoung Seo*, Gyuseong Lee*, Seokju Cho, Jiyoung Lee, Seungryong Kim

AAAI 2023, Feb. 2023

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Semi-Supervised Learning of Semantic Correspondence With Pseudo-Labels

Jiwon Kim*, Kwangrok Ryoo*, Junyoung Seo*, Gyuseong Lee*, Daehwan Kim, Hansang Cho, Seungryong Kim

CVPR 2022, Jun. 2022

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Conmatch: Semi-supervised learning with confidence-guided consistency regularization

Jiwon Kim, Youngjo Min, Daehwan Kim, Gyuseong Lee, Junyoung Seo, Kwangrok Ryoo, Seungryong Kim

ECCV 2022, Oct. 2022

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Towards Flexible Inductive Bias via Progressive Reparameterization Scheduling

Yunsung Lee*, Gyuseong Lee*, Kwangrok Ryoo*, Hyojun Go*, Jihye Park*, Seungryong Kim

ECCV 2022 Workshops on Visual Inductive Priors, Dec. 2022

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AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning

Jiwon Kim, Kwangrok Ryoo, Gyuseong Lee, Seokju Cho, Junyoung Seo, Daehwan Kim, Hansang Cho, Seungryong Kim

arXiv preprint, Jan. 2022

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