Ph.D candidate
Affiliation: Department of ECE, Seoul National University (SNU), Seoul, Korea
Email: dh6dh@snu.ac.kr
Google scholar: profile
I am a Ph.D candidate student majoring in computer vision at SNU computer vision lab, advised by Prof. Kyoung Mu Lee.
Research Interests
My current research focuses on improving efficiency in deep learning.
More specifically, I work on low-rank adaptation for fine-tuning large models on downstream tasks, as well as network pruning and quantization.
My research interests also include continual learning and task-driven image super-resolution.
Publications
- Jaeha Kim, Junghun Oh, and Kyoung Mu Lee, “Exploiting Diffusion Prior for Task-driven Image Restoration”, In International Conference on Computer Vision (ICCV), 2025.
- Junghun Oh, Sungyong Baik, and Kyoung Mu Lee, “Find A Winning Sign: Sign Is All We Need to Win the Lottery”, In International Conference on Learning Representations (ICLR), 2025.
- Cheeun Hong*, Sungyong Baik*, Junghun Oh, and Kyoung Mu Lee, “Difficulty, Diversity, and Plausibility: Dynamic Data-Free Quantization”, In Winter Conference on Applications of Computer Vision (WACV), 2025.
- Junghun Oh*, Sungyong Baik*, and Kyoung Mu Lee, “CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning”, In European Conference on Computer Vision (ECCV), 2024.
- Jaeha Kim, Junghun Oh, and Kyoung Mu Lee, “Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss”, In Computer Vision and Pattern Recognition (CVPR), 2024.
- Junghun Oh, Heewon Kim, Seungjun Nah, Cheeun Hong, Jonghyun Choi and Kyoung Mu Lee, “Attentive Fine-Grained Structured Sparsity for Image Restoration”, In Computer Vision and Pattern Recognition (CVPR), 2022. [PDF], [SUPP], [CODE]
- 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], [SUPP]
- 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]
- Sungyong Baik, Junghun Oh, Seokil Hong, and Kyoung Mu Lee, “Learning to Forget for Meta-Learning via Task-and-Layer-Wise Attenuation”, IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), accepted. [PDF], [SUPP]