SynPo-Net-Accurate and Fast CNN-Based 6DoF Object Pose Estimation Using Synthetic Training.

Su, Yongzhi; Rambach, Jason; Pagani, Alain; Stricker, Didier

Su, Yongzhi; Rambach, Jason; Pagani, Alain; Stricker, Didier.

Afiliación

Su Y; TU Kaiserslautern, 67663 Kaiserslautern, Germany.
Rambach J; German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany.
Pagani A; German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany.
Stricker D; TU Kaiserslautern, 67663 Kaiserslautern, Germany.

Sensors (Basel) ; 21(1)2021 Jan 05.

Article en En | MEDLINE | ID: mdl-33466293

Palabras clave

6DoF object pose; 6DoF object tracking; convolutional neural networks; deep learning; domain adaptation; object pose estimation; training with synthetic images

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Alemania

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