32 citations · 107 across the 20 of their papers we have counts for
4 papers · 1 filter
Exploiting Shape Cues for Weakly Supervised Semantic Segmentation
Sungpil Kho, Pilhyeon Lee, Wonyoung Lee +2
Weakly supervised semantic segmentation (WSSS) aims to produce pixel-wise class predictions with only image-level labels for training. To this end, previous methods adopt the commo…
Exploiting Domain Transferability for Collaborative Inter-level Domain Adaptive Object Detection
Mirae Do, Seogkyu Jeon, Pilhyeon Lee +3
Domain adaptation for object detection (DAOD) has recently drawn much attention owing to its capability of detecting target objects without any annotations. To tackle the problem,…
Fair Contrastive Learning for Facial Attribute Classification
Sungho Park, Jewook Lee, Pilhyeon Lee +3
Learning visual representation of high quality is essential for image classification. Recently, a series of contrastive representation learning methods have achieved preeminent suc…
Inter-subject Contrastive Learning for Subject Adaptive EEG-based Visual Recognition
Pilhyeon Lee, Sunhee Hwang, Jewook Lee +3
This paper tackles the problem of subject adaptive EEG-based visual recognition. Its goal is to accurately predict the categories of visual stimuli based on EEG signals with only a…