Reality Laboratory
숭실대학교 본교(제1캠퍼스) 글로벌미디어학부
김희원 교수
Video Frame Interpolation
Image Enhancement
Few-Shot Learning
발행물
전체 논문
21
1
Learning Controllable ISP for Image Enhancement
Heewon Kim, Kyoung Mu Lee
IEEE Trans. Image Processing (TIP), 2023
2
Learning to Learn Task-Adaptive Hyperparameters for Few-Shot Learning
Sungyong Baik, Myungsub Choi, Janghoon Choi, Heewon Kim, Kyoung Mu Lee
IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), 2023
3
NERDS: A General Framework to Train Camera Denoisers from Raw-RGB Noisy Image Pairs
Heewon Kim, Kyoung Mu Lee
International Conference on Learning Representations (ICLR), 2023
4
Fine-Grained Neural Architecture Search for Image Super-Resolution
Heewon Kim, Seokil Hong, Bohyung Han, Heesoo Myeong, Kyoung Mu Lee
Journal of Visual Communication and Image Representation (JVCI), 2022
5
CADyQ: Content-Aware Dynamic Quantization for Image Super Resolution
Cheeun Hong, Sungyong Baik, Heewon Kim, Seungjun Nah, Kyoung Mu Lee
Proc. European Conference on Computer Vision (ECCV), 2022
6
Machine learning-based predictive modeling of depression in hypertensive populations
Chiyoung Lee, Heewon Kim
PLoS One, 2022
7
Attentive Fine-Grained Structured Sparsity for Image Restoration
Junghun Oh, Heewon Kim, Seungjun Nah, Cheeun Hong, Jonghyun Choi, Kyoung Mu Lee
Proc. Computer Vision and Pattern Recognition (CVPR), 2022
8
DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks
Cheeun Hong, Heewon Kim, Sungyong Baik, Junghun Oh, Kyoung Mu Lee
Winter Conference on Applications of Computer Vision (WACV), 2022
9
Batch Normalization Tells You Which Filter is Important
Junghun Oh, Heewon Kim, Sungyong Baik, Cheeun Hong, Kyoung Mu Lee
Winter Conference on Applications of Computer Vision (WACV), 2022
10
Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning
Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaesik Min, Kyoung Mu Lee
International Conference on Computer Vision (ICCV), 2021