Mixture Dense Regression for Object Detection and Human Pose Estimation

Mixture models are well-established learning approaches that, in computer vision, have mostly been applied to inverse or ill-defined problems. However, they are general-purpose divide-and-conquer techniques, splitting the input space into relatively homogeneous subsets in a data-driven manner. Not o...

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Veröffentlicht in:	arXiv.org 2020-04
Hauptverfasser:	Varamesh, Ali, Tuytelaars, Tinne
Format:	Artikel
Sprache:	eng
Schlagworte:	Collapse Computer vision Ground truth Machine learning Model accuracy Object recognition Probabilistic models Uncertainty
Online-Zugang:	Volltext
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