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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 2020Show all

5 papers · 1 filter

cs.CV2020★ 20 cited

FairFaceGAN: Fairness-aware Facial Image-to-Image Translation

Sunhee Hwang, Sungho Park, Dohyung Kim +2

In this paper, we introduce FairFaceGAN, a fairness-aware facial Image-to-Image translation model, mitigating the problem of unwanted translation in protected attributes (e.g., gen…

cs.CV2020

In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization

Minsong Ki, Youngjung Uh, Wonyoung Lee +1

Weakly supervised object localization (WSOL) aims to localize the target object using only the image-level supervision. Recent methods encourage the model to activate feature maps…

cs.LG2020★ 9 cited

README: REpresentation learning by fairness-Aware Disentangling MEthod

Sungho Park, Dohyung Kim, Sunhee Hwang +1

Fair representation learning aims to encode invariant representation with respect to the protected attribute, such as gender or age. In this paper, we design Fairness-aware Disenta…

cs.CV2020

Weakly-supervised Temporal Action Localization by Uncertainty Modeling

Pilhyeon Lee, Jinglu Wang, Yan Lu +1

Weakly-supervised temporal action localization aims to learn detecting temporal intervals of action classes with only video-level labels. To this end, it is crucial to separate fra…

cs.CV2020★ 32 cited

Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation

Myeongjin Kim, Hyeran Byun

Since annotating pixel-level labels for semantic segmentation is laborious, leveraging synthetic data is an attractive solution. However, due to the domain gap between synthetic do…