Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation

In this work, we introduce Deep Bingham Networks (DBN) , a generic framework that can naturally handle pose-related uncertainties and ambiguities arising in almost all real life applications concerning 3D data. While existing works strive to find a single solution to the pose estimation problem, we...

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Vydané v:	International journal of computer vision Ročník 130; číslo 7; s. 1627 - 1654
Hlavní autori:	Deng, Haowen, Bui, Mai, Navab, Nassir, Guibas, Leonidas, Ilic, Slobodan, Birdal, Tolga
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.07.2022 Springer Springer Nature B.V
Predmet:	Artificial Intelligence Computer Imaging Computer Science Computer vision Datasets Human-computer interaction Image Processing and Computer Vision Machine vision Networks Numerical methods Numerical stability Pattern Recognition Pattern Recognition and Graphics Pose estimation Solution space Special Issue on 3D Computer Vision Three dimensional models Training Uncertainty Vision Camera pose Bingham distribution Uncertainty Point clouds 3D computer vision Uncertainty estimation Camera relocalization Object pose Rotation 6D Posterior distribution Ambiguity
ISSN:	0920-5691, 1573-1405
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