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T-DEED: Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in Sports Videos

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In this paper, we introduce T-DEED, a Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in sports videos. T-DEED addresses multiple challenges in the task, including the need for discriminability among frame representations, high output temporal resolution to maintain prediction precision, and the necessity to capture information at different temporal scales to handle events with varying dynamics. It tackles these challenges through its specifically designed architecture, featuring an encoder-decoder for leveraging multiple temporal scales and achieving high output temporal resolution, along with temporal modules designed to increase token discriminability. Leveraging these characteristics, T-DEED achieves SOTA performance on the FigureSkating and FineDiving datasets. Code is available at https://github.com/arturxe2/T-DEED.

Artur Xarles, Sergio Escalera, Thomas B. Moeslund, Albert Clap\'es• 2024

Related benchmarks

TaskDatasetResultRank
Event SpottingFS-Perf
mAP0.9605
23
Event SpottingFineGYM
mAP66.7
23
Event SpottingComp FS
mAP92.86
23
Action spottingSoccerNet v2 (test)
Average-mAP (Tight 1-5 s)39.43
23
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