4 citations · 6 across the 7 of their papers we have counts for
8 papers
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…
Subject Adaptive EEG-based Visual Recognition
Pilhyeon Lee, Sunhee Hwang, Seogkyu Jeon +1
This paper focuses on EEG-based visual recognition, aiming to predict the visual object class observed by a subject based on his/her EEG signals. One of the main challenges is the…
Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization
Seogkyu Jeon, Kibeom Hong, Pilhyeon Lee +2
Domain generalization aims to enhance the model robustness against domain shift without accessing the target domain. Since the available source domains for training are limited, re…
Learning Action Completeness from Points for Weakly-supervised Temporal Action Localization
Pilhyeon Lee, Hyeran Byun
We tackle the problem of localizing temporal intervals of actions with only a single frame label for each action instance for training. Owing to label sparsity, existing work fails…
Continuous Face Aging Generative Adversarial Networks
Seogkyu Jeon, Pilhyeon Lee, Kibeom Hong +1
Face aging is the task aiming to translate the faces in input images to designated ages. To simplify the problem, previous methods have limited themselves only able to produce disc…