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20192023
most citedLearning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation

32 citations · 107 across the 20 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021

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…

cs.CV2021★ 4 cited

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…

cs.CV2021

Domain-Aware Universal Style Transfer

Kibeom Hong, Seogkyu Jeon, Huan Yang +2

Style transfer aims to reproduce content images with the styles from reference images. Existing universal style transfer methods successfully deliver arbitrary styles to original i…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2021

ArrowGAN : Learning to Generate Videos by Learning Arrow of Time

Kibeom Hong, Youngjung Uh, Hyeran Byun

Training GANs on videos is even more sophisticated than on images because videos have a distinguished dimension: time. While recent methods designed a dedicated architecture consid…