Abstract
This paper addresses the problem of viewpoint estimation of an object in a given image. It presents five key insights and a CNN that is based on them. The network’s major properties are as follows. (i) The architecture jointly solves detection, classification, and viewpoint estimation. (ii) New types of data are added and trained on. (iii) A novel loss function, which takes into account both the geometry of the problem and the new types of data, is propose. Our network allows a substantial boost in performance: from 36.1% gained by SOTA algorithms to 45.9%.
Cite
CITATION STYLE
Divon, G., & Tal, A. (2018). Viewpoint estimation—insights and model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11218 LNCS, pp. 265–281). Springer Verlag. https://doi.org/10.1007/978-3-030-01264-9_16
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
