10 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.CV2024
FREST: Feature RESToration for Semantic Segmentation under Multiple Adverse Conditions
Sohyun Lee, Namyup Kim, Sungyeon Kim +1
Robust semantic segmentation under adverse conditions is crucial in real-world applications. To address this challenging task in practical scenarios where labeled normal condition…
cs.CV2023
Shatter and Gather: Learning Referring Image Segmentation with Text Supervision
Dongwon Kim, Namyup Kim, Cuiling Lan +1
Referring image segmentation, the task of segmenting any arbitrary entities described in free-form texts, opens up a variety of vision applications. However, manual labeling of tra…
cs.CV2022★ 10 cited
ReSTR: Convolution-free Referring Image Segmentation Using Transformers
Namyup Kim, Dongwon Kim, Cuiling Lan +2
Referring image segmentation is an advanced semantic segmentation task where target is not a predefined class but is described in natural language. Most of existing methods for thi…