activity
20172022
most citedDiscover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation

7 citations · 21 across the 11 of their papers we have counts for

collaborators

20 papers

cs.CV2022

Talking Face Generation with Multilingual TTS

Hyoung-Kyu Song, Sang Hoon Woo, Junhyeok Lee +5

In this work, we propose a joint system combining a talking face generation system with a text-to-speech system that can generate multilingual talking face videos from only the tex…

cs.CV20217 cited

Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation

KwanYong Park, Sanghyun Woo, Inkyu Shin +1

Unsupervised domain adaptation (UDA) for semantic segmentation has been attracting attention recently, as it could be beneficial for various label-scarce real-world scenarios (e.g.…

eess.IV20211 cited

Studying the Effects of Self-Attention for Medical Image Analysis

Adrit Rao, Jongchan Park, Sanghyun Woo +2

When the trained physician interprets medical images, they understand the clinical importance of visual features. By applying cognitive attention, they apply greater focus onto cli…

cs.CV20212 cited

LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation

Inkyu Shin, Dong-jin Kim, Jae Won Cho +3

Unsupervised Domain Adaptation (UDA) for semantic segmentation has been actively studied to mitigate the domain gap between label-rich source data and unlabeled target data. Despit…

cs.CV20214 cited

Unsupervised Domain Adaptation for Video Semantic Segmentation

Inkyu Shin, Kwanyong Park, Sanghyun Woo +1

Unsupervised Domain Adaptation for semantic segmentation has gained immense popularity since it can transfer knowledge from simulation to real (Sim2Real) by largely cutting out the…

cs.CV2021

Learning to Associate Every Segment for Video Panoptic Segmentation

Sanghyun Woo, Dahun Kim, Joon-Young Lee +1

Temporal correspondence - linking pixels or objects across frames - is a fundamental supervisory signal for the video models. For the panoptic understanding of dynamic scenes, we f…