most citedFeature Stylization and Domain-aware Contrastive Learning for Domain Generalization

4 citations · 4 across the 2 of their papers we have counts for

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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…