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Sports Video Analysis on Large-Scale Data. (arXiv:2208.04897v1 [cs.CV])
Aug. 10, 2022, 1:12 a.m. | Dekun Wu, He Zhao, Xingce Bao, Richard P. Wildes
cs.CV updates on arXiv.org arxiv.org
This paper investigates the modeling of automated machine description on
sports video, which has seen much progress recently. Nevertheless,
state-of-the-art approaches fall quite short of capturing how human experts
analyze sports scenes. There are several major reasons: (1) The used dataset is
collected from non-official providers, which naturally creates a gap between
models trained on those datasets and real-world applications; (2) previously
proposed methods require extensive annotation efforts (i.e., player and ball
segmentation at pixel level) on localizing useful visual …
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