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TVNet: Temporal Voting Network for Action Localization

2022-01-02 23:46:18
Hanyuan Wang, Dima Damen, Majid Mirmehdi, Toby Perrett

Abstract

We propose a Temporal Voting Network (TVNet) for action localization in untrimmed videos. This incorporates a novel Voting Evidence Module to locate temporal boundaries, more accurately, where temporal contextual evidence is accumulated to predict frame-level probabilities of start and end action boundaries. Our action-independent evidence module is incorporated within a pipeline to calculate confidence scores and action classes. We achieve an average mAP of 34.6% on ActivityNet-1.3, particularly outperforming previous methods with the highest IoU of 0.95. TVNet also achieves mAP of 56.0% when combined with PGCN and 59.1% with MUSES at 0.5 IoU on THUMOS14 and outperforms prior work at all thresholds. Our code is available at this https URL.

Abstract (translated)

URL

https://arxiv.org/abs/2201.00434

PDF

https://arxiv.org/pdf/2201.00434.pdf


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