3 papers
cs.CV2026
Robust Promptable Video Object Segmentation
Sohyun Lee, Yeho Gwon, Lukas Hoyer +3
The performance of promptable video object segmentation (PVOS) models substantially degrades under input corruptions, which prevents PVOS deployment in safety-critical domains. Thi…
cs.LG2025
Enhancing Cost Efficiency in Active Learning with Candidate Set Query
Yeho Gwon, Sehyun Hwang, Hoyoung Kim +2
This paper introduces a cost-efficient active learning (AL) framework for classification, featuring a novel query design called candidate set query. Unlike traditional AL queries r…
cs.CV2025
GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
Sohyun Lee, Yeho Gwon, Lukas Hoyer +1
Improving robustness of the Segment Anything Model (SAM) to input degradations is critical for its deployment in high-stakes applications such as autonomous driving and robotics. O…