用于传球接球者选择的分层控球感知图指针网络
Hierarchical Possession-Aware Graph Pointer Network for Pass Receiver Selection
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中文总结 AI 辅助
针对足球传球接球者选择的部分观测挑战，提出HPGPN模型，通过分层建模实现性能提升，验证了图交互等组件的有效性。
中文摘要 AI 辅助
传球接球者选择是足球分析中的一项基础任务，旨在根据给定比赛状态预测预期接球者。该任务在以事件为中心的静态帧观测、类广播设置下极具挑战性，此类设置仅提供部分且可变的球员可见性，无完整轨迹或稳定球员身份信息，模型需在部分观测下对匿名可见候选球员、对手压力及近期上下文进行推理。为解决该场景，我们提出分层控球感知图指针网络（HPGPN），将传球接球者选择表述为对可见队友的可变大小候选预测。HPGPN联合建模当前球员交互、局部事件上下文及控球级时间动态，用图表示当前传球场景，整合固定事件上下文，并利用动态控球历史捕捉进攻序列的演变过程。通过整合空间、上下文及历史证据分层优化候选表示，再由 glimpse 指针头对候选接球者打分。在公开足球事件及静态帧数据上的实验表明，HPGPN提升了传球接球者选择性能； ablation 研究验证了基于图的交互建模、固定事件上下文及双分支动态控球历史建模的有效性。
英文摘要
Pass receiver selection is a fundamental task in football analytics, aiming to predict the intended receiver under a given game state. This task is challenging with event-centered freeze-frame observations, a broadcast-like setting that provides only partial and variable player visibility without complete trajectories or stable player identities. The model must therefore reason over anonymous visible candidates, opponent pressure, and recent context under partial observation. To address this setting, we propose a Hierarchical Possession-aware Graph Pointer Network (HPGPN), which formulates pass receiver selection as variable-size candidate prediction over visible teammates. HPGPN jointly models current player interactions, local event context, and possession-level temporal dynamics. It represents the current pass situation with a graph, incorporates fixed event context, and uses dynamic possession history to capture how the attacking sequence evolves. Candidate representations are refined hierarchically by integrating spatial, contextual, and historical evidence, and a glimpse pointer head scores the receiver candidates. Experiments on public football event and freeze-frame data show that HPGPN improves pass receiver selection performance. Ablation studies demonstrate the effectiveness of graph-based interaction modeling, fixed event context, and dual-branch dynamic possession-history modeling.
发表机构
- Beijing University of Technology（北京工业大学）
机构由 AI 辅助整理，请以论文原文为准。
