Sports Field Recognition Using Deep Multi-task Learning
Author:
Affiliation:
1. NTT Communications Corporation
Publisher
Information Processing Society of Japan
Subject
General Computer Science
Link
https://www.jstage.jst.go.jp/article/ipsjjip/29/0/29_328/_pdf
Reference32 articles.
1. [1] Theagarajan, R., Pala, F., Zhang, X. and Bhanu, B.: Soccer: Who Has The Ball? Generating Visual Analytics and Player Statistics, CVPR Workshop (2018).
2. [2] Giancola, S., Amine, M., Dghaily, T. and Ghanem, B.: SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos, CVPR Workshop (2018).
3. [3] Homayounfar, N., Fidler, S. and Urtasun, R.: Sports Field Localization via Deep Structured Models, CVPR (2017).
4. [4] Sharma, R.A., Bhat, B., Gandhi, V. and Jawahar, C.V.: Automated Top View Registration of Broadcast Football Videos, WACV (2018).
5. [5] Chen, J. and Little, J.J.: Sports Camera Calibration via Synthetic Data, CVPR Workshop (2019).
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