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Title:

Self6D: Self-Supervised Monocular 6D Object Pose Estimation

Document type:
Konferenzbeitrag
Author(s):
Wang, G.; Manhardt, F.; Shao, J.; Ji, X.; Navab, N.; Tombari, F.
Abstract:
Estimating the 6D object pose is a fundamental problem in computer vision. Convolutional Neural Networks (CNNs) have recently proven to be capable of predicting reliable 6D pose estimates even from monocular images. Nonetheless, CNNs are identified as being extremely data-driven, yet, acquiring adequate annotations is oftentimes very time-consuming and labor intensive. To overcome this shortcoming, we propose the idea of monocular 6D pose estimation by means of self-supervised learning, which er...     »
Keywords:
ECCV,CAMP,CAMPComputerVision,ComputerVision,Rigid3DObjectDetection
Book / Congress title:
The European Conference on Computer Vision (ECCV)
Year:
2020
Notes:
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