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1
LoopDA: Constructing Self-loops to Adapt Nighttime Semantic..:
, In:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
,
Shen, Fengyi
;
Pataki, Zador
;
Gurram, Akhil
... - p. 3255-3265 , 2023
Link:
https://doi.org/10.1109/WACV56688.2023.00327
RT T1 <cTitle>2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)</cTitle>: T1 <Title>LoopDA: Constructing Self-loops to Adapt Nighttime Semantic Segmentation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10030192&Exemplar=1&LAN=DE A1 Shen, Fengyi A1 Pataki, Zador A1 Gurram, Akhil A1 Liu, Ziyuan A1 Wang, He A1 Knoll, Alois YR 2023 SN 2642-9381 K1 Training K1 Adaptation models K1 Computer vision K1 Codes K1 Semantic segmentation K1 Semantics K1 Pipelines K1 Algorithms: Machine learning architectures K1 formulations K1 and algorithms (including transfer) K1 Image recognition and understanding (object detection K1 categorization K1 segmentation K1 scene modeling K1 visual reasoning) SP 3255 OP 3265 LK http://dx.doi.org/https://doi.org/10.1109/WACV56688.2023.00327 DO https://doi.org/10.1109/WACV56688.2023.00327 SF ELIB - SuUB Bremen
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