StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On
Jeongho Kim, Gyojung Gu, Minho Park, Sunghyun Park, and Jaegul Choo
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024, Seattle, Accepted
[Paper] [Project] [Code]

Balanced Learning for Multi-Domain Long-tailed Speaker Recognition
Janghoon Cho*, Sunghyun Park*, Hyunsin Park, Hyoungwoo Park, Seunghan Yang, and Sungrack Yun
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024, Seoul, Accepted
[Paper]

Expression Domain Translation Network for Cross-domain Head Reenactment
Taewoong Kang*, Jeongsik Oh*, Jaeseong Lee, Sunghyun Park, and Jaegul Choo
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024, Seoul, Accepted
[Paper] [Project] [Code]

When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection
Dongmin Kim, Sunghyun Park, and Jaegul Choo
AAAI Conference on Artificial Intelligence (AAAI), 2024, Vancouver, Accepted.
[Paper]

Label Shift Adapter for Test-Time Adaptation under Covariate and Label Shifts
Sunghyun Park, Seunghan Yang, Jaegul Choo, and Sungrack Yun
International Conference on Computer Vision (ICCV), 2023, Paris, Accepted.
[Paper]

Reference-based Image Composition with Sketch via Structure-aware Diffusion Model
Kangyeol Kim, Sunghyun Park, Junsoo Lee, and Jaegul Choo
CVPR Workshop on AI for Content Creation, 2023.
[Paper] [Code]

AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactment
Kangyeol Kim*, Sunghyun Park*, Jaeseong Lee*, Sunghyo Chung, Junsoo Lee, and Jaegul Choo
European Conference on Computer Vision (ECCV), 2022, Tel Aviv, Accepted
Best Paper Award, Korean Artificial Intelligence Association 2022.
[Paper] [Code & Dataset]

High-Resolution Virtual Try-On width Misalignment and Occlusion-Handled Conditions
SangYun Lee*, Gyojung Gu*, Sunghyun Park, Seunghwan Choi, and Jaegul Choo
European Conference on Computer Vision (ECCV), 2022, Tel Aviv, Accepted
[Paper] [Code]

Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment
Chaeyeon Chung*, Taewoo Kim*, Yoonseo Kim*, Sunghyun Park, Kangyeol Kim, and Jaegul Choo
European Conference on Computer Vision (ECCV), 2022, Tel Aviv, Accepted
[Paper]

HairFIT: Pose-invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-region-aware Inpainting
Chaeyeon Chung*, Taewoo Kim*, Hyelin Nam*, Seunghwan Choi, Gyojung Gu, Sunghyun Park, and Jaegul Choo
British Machine Vision Conference (BMVC), 2021, Virtual, Accepted as Oral Presentation.
Best Paper Award, Korean Artificial Intelligence Association 2021.
[Paper]

Continuous-Time Video Generation via Learning Motion Dynamics with Neural ODE
Kangyeol Kim*, Sunghyun Park*, Junsoo Lee, Joonseok Lee, Sookyung Kim, Jaegul Choo, and Edward Choi
British Machine Vision Conference (BMVC), 2021, Virtual, Accepted.
[Paper]

Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children
Jungsoo Lee*, Jooyeol Yun*, Sunghyun Park, Yonggyu Kim, and Jaegul Choo
British Machine Vision Conference (BMVC), 2021, Virtual, Accepted.
[Paper] [Code]

K-Hairstyle: A Large-scale Korean Hairstyle Dataset for Virtual Hair Editing and Hairstyle Classification
Taewoo Kim*, Chaeyeon Chung*, Sunghyun Park*, Gyojung Gu, Keonmin Nam, Wonzo Choe, Jaesung Lee and Jaegul Choo
IEEE International Conference on Image Processing (ICIP), 2021, Virtual, Accepted.
[Paper] [Project & Dataset] [News]

VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization
Seunghwan Choi*, Sunghyun Park*, Minsoo Lee*, and Jaegul Choo
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, Virtual, Accepted (27% acceptance rate).
[Paper] [Project] [Code & Dataset] [PPT]

Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation
Sunghyun Park*, Kangyeol Kim*, Junsoo Lee, Jaegul Choo, Joonseok Lee, Sookyung Kim, and Edward Choi
AAAI Conference on Artificial Intelligence (AAAI), 2021, Virtual, Accepted (21% acceptance rate).
Qualcomm Innovation Fellowship Korea 2021.
[Paper] [Project] [Code & Dataset] [PPT]

Hurricane Nowcasting with Irregular Time-step using Neural-ODE and Video Prediction
Sunghyun Park*, Kangyeol Kim*, Sookyung Kim*, Joonseok Lee, Junsoo Lee, Jiwoo Lee, and Jaegul Choo
International Conference on Learning Representations Workshop (ICLRW), 2020, Accepted as Spotlight Presentation.
[Paper]

PP-VTON: Pose-Preserving Image-based Virtual Try-On Network
Sunghyun Park* and Seunghwan Choi*
Korea Software Congress (KSC), 2019, Pyeongchang, Korea, Accepted.
[Paper]

Learning to Focus and Track Extreme Climate Events
Sookyung Kim*, Sunghyun Park*, Sunghyo Chung*, Joonseok Lee, Yunsung Lee, Hyojin Kim, Mr Prabhat, and Jaegul Choo
British Machine Vision Conference (BMVC), 2019, Cardiff, UK, Accepted as Spotlight Presentation (6.9% acceptance rate for spotlight papers).
ICML 2019 Workshop Climate Change, 2019, California, USA, Accepted.
NIPS 2019 Workshop Tackling Climate Change, 2019, Vancouver, Canada, Accepted.
[Paper]

Improving Scene Text Recognition for Character-Level Long-Tailed Distribution
Sunghyun Park*, Sunghyo Chung*, Jungsoo Lee, and Jaegul Choo
Under Review
[Paper] [Code]

RobustSwap: A Simple yet Robust Face Swapping Model against Attribute Leakage
Jaeseong Lee*, Taewoo Kim*, Sunghyun Park, Younggun Lee, and Jaegul Choo
Under Review
[Paper] [Project]