Joint Negative and Positive Learning for Noisy Labels. - Youngdong Kim; Juseung Yun; Hyounguk Shon; Junmo Kim 002 (CVPR, 2021)

DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning. - Hyounguk Shon; Janghyeon Lee 001; Seung Hwan Kim; Junmo Kim 002 (ECCV (33), 2022)

On the Angular Update and Hyperparameter Tuning of a Scale-Invariant Network. - Juseung Yun; Janghyeon Lee 001; Hyounguk Shon; Eojindl Yi; Seung Hwan Kim; Junmo Kim 002 (ECCV (12), 2022)

UniCLIP: Unified Framework for Contrastive Language-Image Pre-training. - Janghyeon Lee 001; Jongsuk Kim; Hyounguk Shon; Bumsoo Kim; Seung Hwan Kim; Honglak Lee; Junmo Kim 002 (NeurIPS, 2022)

Disposable Transfer Learning for Selective Source Task Unlearning. - Seunghee Koh; Hyounguk Shon; Janghyeon Lee 001; Hyeong Gwon Hong; Junmo Kim 002 (ICCV, 2023)

Lightweight Monocular Depth Estimation via Token-Sharing Transformer. - Dong-Jae Lee; Jae Young Lee 002; Hyounguk Shon; Eojindl Yi; Yeong-Hun Park; Sung-Sik Cho; Junmo Kim 002 (CoRR, 2023)

FRED: Towards a Full Rotation-Equivariance in Aerial Image Object Detection. - Chanho Lee; Jinsu Son; Hyounguk Shon; Yunho Jeon; Junmo Kim 002 (AAAI, 2024)

Neural Vicinal Risk Minimization: Noise-robust Distillation for Noisy Labels. - Hyounguk Shon; Seunghee Koh; Yunho Jeon; Junmo Kim 002 (AISafety@IJCAI, 2024)

Reducing the Content Bias for AI-generated Image Detection. - Seoyeon Gye; Junwon Ko; Hyounguk Shon; Minchan Kwon; Junmo Kim 002 (WACV, 2025)

SFLD: Reducing the content bias for AI-generated Image Detection. - Seoyeon Gye; Junwon Ko; Hyounguk Shon; Minchan Kwon; Junmo Kim 002 (CoRR, 2025)

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization. - Dongyeun Lee; Jiwan Hur; Hyounguk Shon; Jae Young Lee; Junmo Kim (CoRR, 2025)