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Department of Electrical Engineering and Computer Science
Theses
Master
Unsupervised Domain Adaptation for Visual Perception in Various Environments
Changjae Kim
Department of Electrical Engineering and Computer Science
Theses
Master
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Title
Unsupervised Domain Adaptation for Visual Perception in Various Environments
Alternative Title
다양한 환경에서의 시각적 인식을 위한 비지도 도메인 적응 방법
DGIST Authors
Changjae Kim
;
Sunghoon Im
;
Kyong Hwan Jin
Advisor
임성훈
Co-Advisor(s)
Kyong Hwan Jin
Issued Date
2023
Awarded Date
2023-02-01
Citation
Changjae Kim. (2023). Unsupervised Domain Adaptation for Visual Perception in Various Environments. doi: 10.22677/THESIS.200000653655
Type
Thesis
Description
Multi-Target Domain Adaptation,Image-to-Image Translation,Semantic Segmentation,Cross-Domain Correspondence Matching,Cross-Domain Feature Consistency
Table Of Contents
Ⅰ. Introduction 1
Ⅱ. Related Work 3
Ⅲ. Proposed Method 5
3.1 Class-Wise Image Translation 6
3.1.1 High-Precision Pseudo labeling 7
3.1.2 Attribute Transfer 8
3.2 Cross-Domain Feature Consistency for Domain Alignment 9
Ⅳ. Experiments 10
4.1 Datasets 10
4.2 Implementation Details 11
4.3 Synthetic-to-Real Adaptation 11
4.4 Real-to-Real Adaptation 18
4.5 Ablation study on Cross-Domain Feature Consistency 20
Ⅴ. Conclusion 21
Ⅵ. References 22
Ⅶ. 요약문 27
URI
http://hdl.handle.net/20.500.11750/45751
http://dgist.dcollection.net/common/orgView/200000653655
DOI
10.22677/THESIS.200000653655
Degree
Master
Department
Department of Electrical Engineering and Computer Science
Publisher
DGIST
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