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1 Ergebnisse
1
SC-UDA: Style and Content Gaps aware Unsupervised Domain Ad..:
, In:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
,
Yu, Fuxun
;
Wang, Di
;
Chen, Yinpeng
... - p. 1061-1070 , 2022
Link:
https://doi.org/10.1109/WACV51458.2022.00113
RT T1 <cTitle>2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)</cTitle>: T1 <Title>SC-UDA: Style and Content Gaps aware Unsupervised Domain Adaptation for Object Detection</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9706782&Exemplar=1&LAN=DE A1 Yu, Fuxun A1 Wang, Di A1 Chen, Yinpeng A1 Karianakis, Nikolaos A1 Shen, Tong A1 Yu, Pei A1 Lymberopoulos, Dimitrios A1 Lu, Sidi A1 Shi, Weisong A1 Chen, Xiang YR 2022 SN 2642-9381 K1 Computer vision K1 Costs K1 Training data K1 Object detection K1 Detectors K1 Benchmark testing K1 Feature extraction K1 Transfer K1 Few-shot K1 Semi- and Un- supervised Learning Scene Understanding SP 1061 OP 1070 LK http://dx.doi.org/https://doi.org/10.1109/WACV51458.2022.00113 DO https://doi.org/10.1109/WACV51458.2022.00113 SF ELIB - SuUB Bremen
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