| Enhanced deep residual networks for single image super-resolution B Lim, S Son, H Kim, S Nah, K Mu Lee Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 9477 | 2017 |
| Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 2347 | 2017 |
| Channel attention is all you need for video frame interpolation M Choi, H Kim, B Han, N Xu, KM Lee Proceedings of the AAAI conference on artificial intelligence 34 (07), 10663 …, 2020 | 404 | 2020 |
| Meta-learning with task-adaptive loss function for few-shot learning S Baik, J Choi, H Kim, D Cho, J Min, KM Lee Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 209 | 2021 |
| Meta-Learning with Adaptive Hyperparameters S Baik, M Choi, J Choi, H Kim, KM Lee Advances in Neural Information Processing Systems, 2020, 2020 | 200 | 2020 |
| Task-aware image downscaling H Kim, M Choi, B Lim, KM Lee Proceedings of the European conference on computer vision (ECCV), 399-414, 2018 | 120 | 2018 |
| Real-time video super-resolution on smartphones with deep learning, mobile ai 2021 challenge: Report A Ignatov, A Romero, H Kim, R Timofte Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 84 | 2021 |
| Daq: Channel-wise distribution-aware quantization for deep image super-resolution networks C Hong, H Kim, S Baik, J Oh, KM Lee Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 74 | 2022 |
| Machine learning-based predictive modeling of depression in hypertensive populations C Lee, H Kim PLoS One 17 (7), e0272330, 2022 | 69 | 2022 |
| Learning to learn task-adaptive hyperparameters for few-shot learning S Baik, M Choi, J Choi, H Kim, KM Lee IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (3), 1441-1454, 2023 | 63 | 2023 |
| Cadyq: Content-aware dynamic quantization for image super-resolution C Hong, S Baik, H Kim, S Nah, KM Lee European Conference on Computer Vision, 367-383, 2022 | 57 | 2022 |
| Motion-aware dynamic architecture for efficient frame interpolation M Choi, S Lee, H Kim, KM Lee Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 33 | 2021 |
| Attentive fine-grained structured sparsity for image restoration J Oh, H Kim, S Nah, C Hong, J Choi, KM Lee Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 31 | 2022 |
| AIM 2019 challenge on video temporal super-resolution: Methods and results S Nah, S Son, R Timofte, KM Lee, L Siyao, Z Pan, X Xu, W Sun, M Choi, ... 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW …, 2019 | 23 | 2019 |
| Fine-grained neural architecture search for image super-resolution H Kim, S Hong, B Han, H Myeong, KM Lee Journal of Visual Communication and Image Representation 89, 103654, 2022 | 21* | 2022 |
| Batch normalization tells you which filter is important J Oh, H Kim, S Baik, C Hong, KM Lee Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 15 | 2022 |
| Learning controllable isp for image enhancement H Kim, KM Lee IEEE Transactions on Image Processing 33, 867-880, 2023 | 11* | 2023 |
| Searching for controllable image restoration networks H Kim, S Baik, M Choi, J Choi, KM Lee Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 11 | 2021 |
| Machine learning-based etiologic subtyping of ischemic stroke using circulating exosomal microRNAs JH Bang, EH Kim, HJ Kim, JW Chung, WK Seo, GM Kim, DH Lee, H Kim, ... International Journal of Molecular Sciences 25 (12), 6761, 2024 | 5 | 2024 |
| DynScene: Scalable Generation of Dynamic Robotic Manipulation Scenes for Embodied AI S Lee, S Park, H Kim Proceedings of the Computer Vision and Pattern Recognition Conference, 12166 …, 2025 | 3 | 2025 |
Kyoung Mu LeeProfessor, Department of Electrical and Computer Engineering, Seoul National UniversityVerified email at snu.ac.kr
