Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup-Reference-Cited by-同舟云学术

Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports - MMSports '19
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Author:

Van Zandycke Gabriel¹,De Vleeschouwer Christophe¹

Affiliation:

1. Université catholique de Louvain, Louvain-la-Neuve, Belgium

Funder

Keemotion

Region Wallonne

Publisher

ACM Press

Reference47 articles.

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2. Oles Andrienko. 2019. ICNet and PSPNet-50 in Tensorflow for real-time semantic segmentation. https://github.com/oandrienko/fast-semantic-segmentation .

3. Murat Seckin Ayhan and Berens P.. 2018. Test-time Data Augmentation for Estimation of Heteroscedastic Aleatoric Uncertainty in Deep Neural Networks. In MIDL .

4. B. Chakraborty and S. Meher. 2013. A real-time trajectory-based ball detection-and-tracking framework for basketball video . Journal of Optics (2013).

5. F. Chen and C. De Vleeschouwer. 2010. Personalized production of basketball videos from multi-sensored data under limited display resolution . CVIU (2010).

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