no code implementations • 20 Dec 2023 • Byung Hyun Lee, Min-hwan Oh, Se Young Chun
Specifically, for input perturbation, we propose an approximate perturbation method that injects noise into the input data as well as the feature vector and then interpolates the two perturbed samples.
no code implementations • ICCV 2023 • Byung Hyun Lee, Okchul Jung, Jonghyun Choi, Se Young Chun
To address this challenge, we propose a novel multi-level hierarchical class incremental task configuration with an online learning constraint, called hierarchical label expansion (HLE).
no code implementations • CVPR 2023 • Dongwon Park, Byung Hyun Lee, Se Young Chun
Image restorations for single degradations have been widely studied, demonstrating excellent performance for each degradation, but can not reflect unpredictable realistic environments with unknown multiple degradations, which may change over time.
no code implementations • 7 Feb 2019 • Byung Hyun Lee, Se Young Chun
Recently, deep neural networks (DNNs) have shown advantages in accelerating optimization algorithms.