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English(EN) Decoupling Spatio-Temporal Adapter for Fine-Grained Badminton Action Localization

新型适配器改进羽毛球视频中的细粒度动作定位

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种名为解耦时空适配器（DSTA）的新方法，以改进专业羽毛球视频中细粒度动作的定位。该方法通过将运动表示分解为时间、垂直和水平空间变化来有效地模拟复杂时空动态。DSTA方法在新的基准数据集Fine-Badminton和现有的ShuttleSet基准上取得了最先进的性能，同时在计算和参数成本方面保持了效率。 AI

影响 增强了体育运动中的细粒度动作识别，可能改进体育分析和训练工具。

排序理由 该集群包含一篇学术论文，详细介绍了一种用于特定计算机视觉任务的新方法和数据集。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Tianyu Wang (School of Economics and Management, Beihang University, Beijing 100191, China), Junjie Wu (School of Economics and Management, Beihang University, Beijing 100191, China, Key Laboratory of Data Intelligence and Management, Beihang University,… ·

    Decoupling Spatio-Temporal Adapter for Fine-Grained Badminton Action Localization

    arXiv:2605.23355v1 Announce Type: cross Abstract: Temporal Action Localization (TAL) has been extensively studied in generic video understanding, while fine-grained sports scenarios, such as professional badminton, remain underexplored due to their complex and subtle spatio-tempo…

  2. arXiv cs.CV TIER_1 English(EN) · Shishuo Li ·

    Decoupling Spatio-Temporal Adapter for Fine-Grained Badminton Action Localization

    Temporal Action Localization (TAL) has been extensively studied in generic video understanding, while fine-grained sports scenarios, such as professional badminton, remain underexplored due to their complex and subtle spatio-temporal dynamics. In this paper, we focus on fine-grai…

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