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

Estimation and tracking of 6DoF poses of objects in images is a challenging problem of great importance for robotic interaction and augmented reality. Recent approaches applying deep neural networks for pose estimation have shown encouraging results. However, most of them rely on training with real...

Whakaahuatanga katoa

I tiakina i:

Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua:	Yongzhi Su, Jason Rambach, Alain Pagani, Didier Stricker
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	MDPI AG 2021-01-01
Rangatū:	Sensors
Ngā marau:	object pose estimation convolutional neural networks training with synthetic images deep learning domain adaptation 6DoF object pose
Urunga tuihono:	https://www.mdpi.com/1424-8220/21/1/300
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

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

Ngā tūemi rite