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1 Ergebnisse
1
SynDa: A Novel Synthetic Data Generation Pipeline for Activ..:
, In:
2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)
,
Rajendran, Megani
;
Tan, Chek Tien
;
Atmosukarto, Indriyati
.. - p. 373-377 , 2022
Link:
https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00081
RT T1 <cTitle>2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)</cTitle>: T1 <Title>SynDa: A Novel Synthetic Data Generation Pipeline for Activity Recognition</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9974180&Exemplar=1&LAN=DE A1 Rajendran, Megani A1 Tan, Chek Tien A1 Atmosukarto, Indriyati A1 Ng, Aik Beng A1 See, Simon YR 2022 SN 2771-1110 K1 Costs K1 Pipelines K1 Pose estimation K1 Streaming media K1 Rendering (computer graphics) K1 Data models K1 Human activity recognition K1 Activity recognition-Computer vision-Elderly-Activities of daily living K1 Skeletal pose estimation-Pose tracking-Photorealistic RTX rendering- K1 Synthetic data generation-Synthetic data-Pipeline-Synthetic data for ADL SP 373 OP 377 LK http://dx.doi.org/https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00081 DO https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00081 SF ELIB - SuUB Bremen
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