NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study. - Seungjun Nah; Sungyong Baik; Seokil Hong; Gyeongsik Moon; Sanghyun Son 002; Radu Timofte; Kyoung Mu Lee (CVPR Workshops, 2019)

NTIRE 2019 Challenge on Video Deblurring: Methods and Results. - Seungjun Nah; Radu Timofte; Sungyong Baik; Seokil Hong; Gyeongsik Moon; Sanghyun Son 002; Kyoung Mu Lee; Xintao Wang 002; Kelvin C. K. Chan; Ke Yu; Chao Dong 005; Chen Change Loy; et al. (CVPR Workshops, 2019)

NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results. - Seungjun Nah; Radu Timofte; Shuhang Gu; Sungyong Baik; Seokil Hong; Gyeongsik Moon; Sanghyun Son 002; Kyoung Mu Lee; Xintao Wang 002; Kelvin C. K. Chan; Ke Yu; Chao Dong 005; et al. (CVPR Workshops, 2019)

Learning to Remember Past to Predict Future for Visual Tracking. - Sungyong Baik; Junseok Kwon; Kyoung Mu Lee (ICIP, 2019)

Domain Adaptation of Learned Featuresfor Visual Localization. - Sungyong Baik; Hyo Jin Kim 004; Tianwei Shen; Eddy Ilg; Kyoung Mu Lee; Christopher Sweeney (BMVC, 2020)

Learning to Forget for Meta-Learning. - Sungyong Baik; Seokil Hong; Kyoung Mu Lee (CVPR, 2020)

Scene-Adaptive Video Frame Interpolation via Meta-Learning. - Myungsub Choi; Janghoon Choi; Sungyong Baik; Tae Hyun Kim 006; Kyoung Mu Lee (CVPR, 2020)

Meta-Learning with Adaptive Hyperparameters. - Sungyong Baik; Myungsub Choi; Janghoon Choi; Heewon Kim; Kyoung Mu Lee (NeurIPS, 2020)

Domain Adaptation of Learned Features for Visual Localization. - Sungyong Baik; Hyo Jin Kim 004; Tianwei Shen; Eddy Ilg; Kyoung Mu Lee; Chris Sweeney (CoRR, 2020)

Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning. - Sungyong Baik; Janghoon Choi; Heewon Kim; Dohee Cho; Jaesik Min; Kyoung Mu Lee (ICCV, 2021)

Searching for Controllable Image Restoration Networks. - Heewon Kim; Sungyong Baik; Myungsub Choi; Janghoon Choi; Kyoung Mu Lee (ICCV, 2021)

CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution. - Cheeun Hong; Sungyong Baik; Heewon Kim; Seungjun Nah; Kyoung Mu Lee (ECCV (7), 2022)

DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks. - Cheeun Hong; Heewon Kim; Sungyong Baik; Junghun Oh; Kyoung Mu Lee (WACV, 2022)

Batch Normalization Tells You Which Filter is Important. - Junghun Oh; Heewon Kim; Sungyong Baik; Cheeun Hong; Kyoung Mu Lee (WACV, 2022)

Visual Tracking by Adaptive Continual Meta-Learning. - Janghoon Choi; Sungyong Baik; Myungsub Choi; Junseok Kwon; Kyoung Mu Lee (IEEE Access, 2022)

Learning to Forget for Meta-Learning via Task-and-Layer-Wise Attenuation. - Sungyong Baik; Junghoon Oh; Seokil Hong; Kyoung Mu Lee (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Test-Time Adaptation for Video Frame Interpolation via Meta-Learning. - Myungsub Choi; Janghoon Choi; Sungyong Baik; Tae Hyun Kim 006; Kyoung Mu Lee (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Deep Variational Bayesian Modeling of Haze Degradation Process. - Eun Woo Im; Junsung Shin; Sungyong Baik; Tae Hyun Kim 006 (CIKM, 2023)

Semantic-Aware Dynamic Parameter for Video Inpainting Transformer. - Eunhye Lee; Jinsu Yoo; Yunjeong Yang; Sungyong Baik; Tae Hyun Kim 006 (ICCV, 2023)

Learning Controllable Degradation for Real-World Super-Resolution via Constrained Flows. - Seobin Park; Dongjin Kim 004; Sungyong Baik; Tae Hyun Kim 006 (ICML, 2023)

SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection. - Daehyun Kim; Sungyong Baik; Tae Hyun Kim 006 (NeurIPS, 2023)

LAN: Learning to Adapt Noise for Image Denoising. - Changjin Kim; Tae Hyun Kim 006; Sungyong Baik (CVPR, 2024)

CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning. - Junghun Oh; Sungyong Baik; Kyoung Mu Lee (ECCV (49), 2024)

sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows. - Dongjin Kim 004; Donggoo Jung; Sungyong Baik; Tae Hyun Kim 006 (ICLR, 2024)

Rethinking RGB Color Representation for Image Restoration Models. - Jaerin Lee; JoonKyu Park; Sungyong Baik; Kyoung Mu Lee (CoRR, 2024)

LAN: Learning to Adapt Noise for Image Denoising. - Changjin Kim; Tae Hyun Kim; Sungyong Baik (CoRR, 2024)

Looking beyond input frames: Self-supervised adaptation for video super-resolution. - Jinsu Yoo; Jihoon Nam; Sungyong Baik; Tae Hyun Kim 006 (Pattern Recognit., 2024)

CoLaNet: Adaptive Context and Latent Information Blending for Face Image Inpainting. - Joonkyu Park; Cheeun Hong; Sungyong Baik; Kyoung Mu Lee (IEEE Signal Process. Lett., 2024)

Learning to Learn Task-Adaptive Hyperparameters for Few-Shot Learning. - Sungyong Baik; Myungsub Choi; Janghoon Choi; Heewon Kim; Kyoung Mu Lee (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

SeeDiff: Off-the-Shelf Seeded Mask Generation from Diffusion Models. - Joon Hyun Park; Kumju Jo; Sungyong Baik (AAAI, 2025)

Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning. - Yeoreum Lee; Jinwook Jung; Sungyong Baik (ICLR, 2025)

Find A Winning Sign: Sign Is All We Need to Win the Lottery. - Junghun Oh; Sungyong Baik; Kyoung Mu Lee (ICLR, 2025)

Difficulty, Diversity, and Plausibility: Dynamic Data-Free Quantization. - Cheeun Hong; Sungyong Baik; Junghun Oh; Kyoung Mu Lee (WACV, 2025)

MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields. - Jaeyoung Chung 002; Kanggeon Lee; Sungyong Baik; Kyoung Mu Lee (IEEE Access, 2025)

CoAPT: Context Attribute words for Prompt Tuning. - Gun Lee 002; Subin An; Sungyong Baik; Soochahn Lee (Knowl. Based Syst., 2025)