SGA-INTERACT: A 3D Skeleton-based Benchmark for Group Activity Understanding in Modern Basketball Tactic

• URL: http://arxiv.org/abs/2503.06522v1
• Date: Sun, 09 Mar 2025 08:53:32 GMT
• Title: SGA-INTERACT: A 3D Skeleton-based Benchmark for Group Activity Understanding in Modern Basketball Tactic
• Authors: Yuchen Yang, Wei Wang, Yifei Liu, Linfeng Dong, Hao Wu, Mingxin Zhang, Zhihang Zhong, Xiao Sun,
• Abstract summary: Group Activity Understanding is predominantly studied as Group Activity Recognition task.<n>SGA-INTERACT is the first 3D skeleton-based benchmark for group activity understanding.<n>One2Many is a novel framework that employs a pretrained 3D skeleton backbone for unified individual feature extraction.
• Score: 14.754589492355423
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Group Activity Understanding is predominantly studied as Group Activity Recognition (GAR) task. However, existing GAR benchmarks suffer from coarse-grained activity vocabularies and the only data form in single-view, which hinder the evaluation of state-of-the-art algorithms. To address these limitations, we introduce SGA-INTERACT, the first 3D skeleton-based benchmark for group activity understanding. It features complex activities inspired by basketball tactics, emphasizing rich spatial interactions and long-term dependencies. SGA-INTERACT introduces Temporal Group Activity Localization (TGAL) task, extending group activity understanding to untrimmed sequences, filling the gap left by GAR as a standalone task. In addition to the benchmark, we propose One2Many, a novel framework that employs a pretrained 3D skeleton backbone for unified individual feature extraction. This framework aligns with the feature extraction paradigm in RGB-based methods, enabling direct evaluation of RGB-based models on skeleton-based benchmarks. We conduct extensive evaluations on SGA-INTERACT using two skeleton-based methods, three RGB-based methods, and a proposed baseline within the One2Many framework. The general low performance of baselines highlights the benchmark's challenges, motivating advancements in group activity understanding.

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