2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2026
CD-FKD: Cross-Domain Feature Knowledge Distillation for Robust Single-Domain Generalization in Object Detection
Junseok Lee, Sungho Shin, Seongju Lee +1
Single-domain generalization is essential for object detection, particularly when training models on a single source domain and evaluating them on unseen target domains. Domain shi…
cs.CV2024★ 2 cited
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise
Yeonguk Yu, Minhwan Ko, Sungho Shin +2
Deep neural networks have demonstrated remarkable performance in various vision tasks, but their success heavily depends on the quality of the training data. Noisy labels are a cri…
cs.CV2024
Domain-Specific Block Selection and Paired-View Pseudo-Labeling for Online Test-Time Adaptation
Yeonguk Yu, Sungho Shin, Seunghyeok Back +3
Test-time adaptation (TTA) aims to adapt a pre-trained model to a new test domain without access to source data after deployment. Existing approaches typically rely on self-trainin…