Cheeun Hong


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Ph.D candidate
Affiliation: Department of ECE, Seoul National University (SNU), Seoul, Korea
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I am a Ph.D student majoring in computer vision at SNU computer vision lab, advised by Prof. Kyoung Mu Lee.

Research Interests

I am interested in efficient deep learning and low-level image restoration problems, such as image super-resolution, to handle practical issues in deep learning. Recently I am mainly working on designing lightweight networks for low-level image restoration problems with network optimization and acceleration techniques, especially quantization.


Cheeun Hong, Sungyong Baik, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee, “CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution,” European Conference on Computer Vision (ECCV), 2022. [PDF] [GitHub]

Junghun Oh, Heewon Kim, Seungjun Nah, Cheeun Hong, Jonghyun Choi, and Kyoung Mu Lee,”Attentive Fine-Grained Structured Sparsity for Image Restoration,” Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [PDF] [GitHub]

Cheeun Hong, Heewon Kim, Sungyong Baik, Junghun Oh, and Kyoung Mu Lee, “DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks,” Winter Conference on Applications of Computer Vision (WACV), 2022. [PDF] [GitHub] [YouTube]

Junghun Oh, Heewon Kim, Sungyong Baik, Cheeun Hong, and Kyoung Mu Lee, “Batch Normalization Tells You Which Filter is Important”, Winter Conference on Applications of Computer Vision (WACV), 2022. [PDF]

Awards and Honors