Seunggi Moon — accepted AI-conference papers

2026

AHS: Adaptive Head Synthesis via Synthetic Data Augmentations

Taewoong Kang, Hyojin Jang, Sohyun Jeong, Seunggi Moon, Gihwi Kim, Hoon Jin Jung +1

CVPR 2026

Recent digital media advancements have created increasing demands for sophisticated portrait manipulation techniques, particularly head swapping--where one image's head is seamlessly integrated onto another's body. Current approaches predominantly rely on face-centered cropped data with limited view

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2026

uCLIP: Parameter-Efficient Multilingual Extension of Vision-Language Models with Unpaired Data

Dahyun Chung, Donghyun Shin, Yujin Sung, Seunggi Moon, Jinwoo Jeon, Byung-Jun Lee

AAAI 2026technical

Contrastive Language–Image Pre-training (CLIP) has demonstrated strong generalization across a wide range of visual tasks by leveraging large-scale English–image pairs. However, its extension to low-resource languages remains limited due to the scarcity of high-quality multilingual image–text data.

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