4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CV2023
Improving Diversity in Zero-Shot GAN Adaptation with Semantic Variations
Seogkyu Jeon, Bei Liu, Pilhyeon Lee +3
Training deep generative models usually requires a large amount of data. To alleviate the data collection cost, the task of zero-shot GAN adaptation aims to reuse well-trained gene…
cs.CV2021★ 4 cited
Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization
Seogkyu Jeon, Kibeom Hong, Pilhyeon Lee +2
Domain generalization aims to enhance the model robustness against domain shift without accessing the target domain. Since the available source domains for training are limited, re…