扩展的OpenTTGames数据集：一款乒乓球数据集，用于细粒度击球类型和比分结果
Extended OpenTT Games Dataset: A table tennis dataset for fine-grained shot type and point outcome
AI总结：
扩展OpenTTGames数据集，提供细粒度击球类型和比分结果标注，用于提升乒乓球视频分析的战术理解能力。
摘要：
自动检测和分类乒乓球视频中的击球动作可以简化训练流程，丰富转播叠加内容，并启用细粒度的性能分析。为了实现这一点，需要标注的乒乓球视频数据。我们扩展了公开的OpenTTGames数据集，添加了高度详细的、帧准确的击球类型注释（正手、反手及其子类型）、球员姿态标签（身体倾斜和腿部站姿）以及比赛结果标签在点结束时。OpenTTGames是一组从桌子侧面录制的视频，具有官方标注的击球点、球在网上方或击中网的情况。该数据集已经包含接近事件的球坐标，这些坐标在原始OpenTTGames数据集中要么是
英文摘要：
Automatically detecting and classifying strokes in table tennis video can streamline training workflows, enrich broadcast overlays, and enable fine-grained performance analytics. For this to be possible, annotated video data of table tennis is needed. We extend the public OpenTTGames dataset with highly detailed, frame-accurate shot type annotations (forehand, backhand with subtypes), player posture labels (body lean and leg stance), and rally outcome tags at point end. OpenTTGames is a set of recordings from the side of the table with official labels for bounces, when the ball is above the net, or hitting the net. The dataset already contains ball coordinates near events, which are either "bounce", "net", or "empty_event" in the original OpenTTGames dataset, and semantic masks (humans, table, scoreboard). Our extension adds the types of stroke to the events and a per-player taxonomy so models can move beyond event spotting toward tactical understanding (e.g., whether a stroke is likely to win the point or set up an advantage). We provide a compact coding scheme and code-assisted labeling procedure to support reproducible annotations and baselines for fine-grained stroke understanding in racket sports. This fills a practical gap in the community, where many prior video resources are either not publicly released or carry restrictive/unclear licenses that hinder reuse and benchmarking. Our annotations are released under the same CC BY-NC-SA 4.0 license as OpenTTGames, allowing free non-commercial use, modification, and redistribution, with appropriate attribution.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
