Donghyun Na — accepted AI-conference papers

2024

SwitchLight: Co-design of Physics-driven Architecture and Pre-training Framework for Human Portrait Relighting

Hoon Kim, Minje Jang, Wonjun Yoon, Jisoo Lee, Donghyun Na, Sanghyun Woo

CVPR 2024highlight

We introduce a co-designed approach for human portrait relighting that combines a physics-guided architecture with a pre-training framework. Drawing on the Cook-Torrance reflectance model we have meticulously configured the architecture design to precisely simulate light-surface interactions. Furthe…

Cited by 19 Source ↗PDF ↗Scholar ↗

2020

Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks

Hae Beom Lee, Hayeon Lee, Donghyun Na, Saehoon Kim, Minseop Park, Eunho Yang +1

ICLR 2020talk

While tasks could come with varying the number of instances and classes in realistic settings, the existing meta-learning approaches for few-shot classification assume that number of instances per task and class is fixed. Due to such restriction, they learn to equally utilize the meta-knowledge acro…

Cited by 144 Source ↗code ↗Scholar ↗