Muhammad Kashif Ali, Eun Woo Im, Dongjin Kim, Tae Hyun Kim, Harnessing Meta-Learning for Improving Full-Frame Video Stabilization, Computer Vision and Pattern Recognition (CVPR), 2024.

Changjin Kim, Tae Hyun Kim, Sungyong Baik, LAN: Learning to Adapt Noise for Image Denoising, Computer Vision and Pattern Recognition (CVPR), 2024.

Dongjin Kim*, Donggoo Jung*, Sungyong Baik, Tae Hyun Kim, sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows, International Conference on Learning Representations (ICLR), 2024. [pdf] (accepted)

Young Jae Oh, Jihun Kim, Tae Hyun Kim, "Efficient Model Agnostic Approach for Implicit Neural Representation Based Arbitrary-Scale Image Super-Resolution," arXiv, 2023. [pdf]

Daehyun Kim, Sungyong Baik, Tae Hyun Kim, "SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection," Neural Information Processing Systems (NeurIPS), 2023. [pdf] [project page]

Eun Woo Im*, Junsung Shin*, Sungyong Baik, Tae Hyun Kim, "Deep Variational Bayesian Modeling of Haze Degradation Process,"ACM International Conference on Information and Knowledge Management (CIKM), 2023. (Long Paper) [pdf] [project page]

Muhammad Kashif Ali, Dongjin Kim, Tae Hyun Kim, "Task Agnostic Restoration of Natural Video Dynamics," International Conference on Computer Vision (ICCV), 2023. [pdf]

Eunhye Lee*, Jinsu Yoo*, Yunjeong Yang, Sungyong Baik, Tae Hyun Kim, "Semantic-Aware Dynamic Parameter for Video Inpainting Transformer," International Conference on Computer Vision (ICCV), 2023. [pdf]

Seobin Park*, Dongjin Kim*, Sungyong Baik, Tae Hyun Kim, "Learning Controllable Degradation for Real-World Super-Resolution via Constrained Flows," International Conference on Machine Learning (ICML), 2023. [pdf] [code]

Chaerin Min, Tae Hyun Kim, Jongwoo Lim, "Meta-Learning for Adaptation of Deep Optical Flow Networks," Winter Conference on Applications of Computer Vision (WACV), 2023. [pdf]

Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim, "Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution," Winter Conference on Applications of Computer Vision (WACV), 2023. [pdf] [project page]

Seunghwan Lee, Tae Hyun Kim, "NoiseTransfer: Image Noise Generation with Contrastive Embeddings," Asian Conference on Computer Vision (ACCV), 2022. (oral) [pdf]

Seobin Park, Tae Hyun Kim, "Progressive Image Super-Resolution via Neural Differential Equation," International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022. [pdf]

Muhammad Kashif Ali*, Sangjoon Yu*, Tae Hyun Kim, "Deep Motion Blind Video Stabilization," The British Machine Vision Conference (BMVC), 2021. [pdf] [project page]

Seunghwan Lee, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim, "Restore from Restored: Video Restoration with Pseudo Clean Video," Computer Vision and Pattern Recognition (CVPR), 2021. [pdf] [project page]

Seobin Park*, Jinsu Yoo*, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim, "Fast Adaptation to Super-Resolution Networks via Meta-Learning," European Computer Vision Conference (ECCV), 2020. [pdf] [project page]

Myungsub Choi, Janghoon Choi, Sungyong Baik, Tae Hyun Kim, Kyoung Mu Lee, "Scene-Adaptive Video Frame Interpolation via Meta-Learning," Computer Vision and Pattern Recognition (CVPR), 2020. [pdf] [project page]

Tae Hyun Kim, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Schölkopf, "Spatio-temporal Transformer Network for Video Restoration," European Computer Vision Conference (ECCV), 2018. [pdf]

Tae Hyun Kim, Kyoung Mu Lee, Bernhard Schölkopf, Michael Hirsch, "Online Video Deblurring via Dynamic Temporal Blending Network," International Conference on Computer Vision (ICCV), 2017. [pdf]

Seungjun Nah, Tae Hyun Kim, Kyoung Mu Lee , "Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring," Computer Vision and Pattern Recognition (CVPR), 2017. (spotlight) [pdf] [project page]

Tae Hyun Kim, Kyoung Mu Lee, "Generalized Video Deblurring for Dynamic Scenes," Computer Vision and Pattern Recognition (CVPR), 2015. (oral) [pdf] [project page]

Tae Hyun Kim, Kyoung Mu Lee, "Segmentation-Free Dynamic Scene Deblurring," Computer Vision and Pattern Recognition (CVPR), 2014. (oral) [pdf]

Tae Hyun Kim, Byeongjoo Ahn, Kyoung Mu Lee, "Dynamic Scene Deblurring," International Conference on Computer Vision (ICCV), 2013. [pdf]

Tae Hyun Kim, Hee Seok Lee, Kyoung Mu Lee, "Optical Flow via Locally Adaptive Fusion of Complementary Data Costs," International Conference on Computer Vision (ICCV), 2013. [pdf]

Jinsu Yoo, Jihoon Nam, Sungyong Baik, Tae Hyun Kim, "Looking Beyond Input Frames: Self-Supervised Adaptation for Video Super-Resolution," Pattern Recognition. 2024. (Accepted) [pdf]

Seung Hyun Kim*, Yoon Ju Oh*, Joonhyuk Son*, Donggoo Jung, Daehyun Kim, Soo Rack Ryu, Jae Yoon Na, Jae Kyoon Hwang, Tae Hyun Kim, Hyun-Kyung Park, "Machine Learning-based Analysis for Prediction of Surgical Necrotizing Enterocolitis in Very Low Birth Weight Infants Using Perinatal Factors: A Nationwide Cohort Study," European Journal of Pediatric. 2024. 

Jae-Won Lee, Jong-Hyun Won, Seonggwang Jeon, Yujin Choo, Yubin Yeon, Jin-Seon Oh, Minsoo Kimm, SeonHwa Kim, InSuk Joung, Cheongjae Jang, Sung Jong Lee, Tae Hyun Kim, Kyong Hwan Jin, Giltae Song, Eun-Sol Kim, Jejoong Yoo, Eunok Paek, Yung-Kyun Noh, Keehyoung Joo, "DeepFold: Enhancing Protein Structure Prediction through Optimized Loss Functions, Improved Template Features, and Re-optimized Energy Function," Bioinformatics, 2023. (pdf)

Jae Yoon Na*, Donggoo Jung*, Jong Ho Cha, Daehyun Kim, Joonhyuk Son, Jae Kyoon Hwang, Tae Hyun Kim, Hyun-Kyung Park, "Learning-based longitudinal prediction models for mortality risk in very-low-birth-weight infants: A nationwide cohort study," Neonatology, 2023. (pdf)

Jae Kyoon Hwang*, Dae Hyun Kim*, Jae Yoon Na, Joonhyuk Son, Yoon Ju Oh, Donggoo Jung, Chang-Ryul Kim, Tae Hyun Kim, Hyun-Kyung Park, "Two-stage Learning-based Prediction of Bronchopulmonary Dysplasia in Very Low Birth Weight Infants: A Nationwide Cohort Study," Frontiers in Pediatrics, 2023. [pdf]

Dong Keon Lee*, Jin Hyuk Kim*, Jaehoon Oh, Tae Hyun Kim, Myeong Seong Yoon, Dong Jin Im, Jae Ho Chung, Hayoung Byun, "Detection of acute thoracic aortic dissection based on plain chest radiography and a residual neural network (Resnet)," Scientific Reports, 2022. [pdf]

Myungsub Choi, Janghoon Choi, Sungyong Baik, Tae Hyun Kim, Kyoung Mu Lee, "Test-Time Adaptation for Video Frame Interpolation via Meta-Learning," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022. [pdf] [project page]

Hayoung Byun, Seung Hwan Lee, Tae Hyun Kim, Jaehoon Oh, Jae Ho Chung, "Feasibility of the Machine Learning Network to Diagnose Tympanic Membrane Lesions without Coding Experience," Journal of Personalized Medicine, 2022. [pdf]

Heui Chul Jung*, Changjin Kim*, Jaehoon Oh, Tae Hyun Kim, Beomgyu Kim, Juncheol Lee, Jae Ho Chung, Hayoung Byun, Myeong Seong Yoon, Dong Keon Lee, "Position Classification of the Endotracheal Tube with Automatic Segmentation of the Trachea and the Tube on Plain Chest Radiography Using Deep Convolutional Neural Network," Journal of Personalized Medicine, 2022. [pdf]

Byungjoo Chae, Jinsun Park, Tae Hyun Kim, Donghyeon Cho, "Online Learning for Reference-Based Super-Resolution," Electronics, 2022. [pdf]

Joonhyuk Son*, Daehyun Kim*, Jae Yoon Na, Donggoo Jung, Ja-Hye Ahn, Tae Hyun Kim, Hyun-Kyung Park, "Development of artificial neural networks for early prediction of intestinal perforation in preterm infants," Scientific Reports, 2022. [pdf]

Jonathan Samuel Lumentut, Matthew Marchellus, Joshua Santoso, Tae Hyun Kim, Ju Yong Chang, In Kyu Park, "Universal Framework for Joint Image Restoration and 3D Body Reconstruction," IEEE Access, 2021. [pdf]

Junwon Bae*, Sangjoon Yu*, Jaehoon Oh, Tae Hyun Kim, Jae Ho Chung, Hayoung Byun, Myeong Seong Yoon, Chiwon Ahn, Dong Keon Lee, "External validation of deep learning algorithm for detecting and visualizing femoral neck fracture including displaced and non-displaced fracture on plain X-ray," Journal of Digital Imaging, 2021. [pdf]

Hayoung Byun*, Sangjoon Yu*, Jaehoon Oh, Junwon Bae, Myeong Seong Yoon, Seung Hwan Lee, Jae Ho Chung, Tae Hyun Kim, "An Assistive Role of a Machine Learning Network in Diagnosis of Middle Ear Diseases," Journal of Clinical Medicine, 2021. [pdf]

Jonathan Samuel Lumentut, Tae Hyun Kim, Ravi Ramamoorthi, In Kyu Park, "Deep recurrent network for fast and full-resolution light field deblurring," IEEE Signal Processing Letters, 2019. [pdf]

Tae Hyun Kim, Seungjun Nah, Kyoung Mu Lee, "Dynamic Video Deblurring Using a Locally Adaptive Blur Model," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2018. [pdf] [project page]

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