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Group Activity Recognition On Volleyball

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
Tamura et al.96.0Hunting Group Clues with Transformers for Social Group Activity Recognition-
DIN (VGG16)93.6Spatio-Temporal Dynamic Inference Network for Group Activity Recognition
PoseC3D (Pose-Only)91.3Revisiting Skeleton-based Action Recognition
H-LSTCM88.4Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition-
COMPOSER94.69COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality
CHASE(CTR-GCN)92.89CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
Zappardino et al.91.0Learning Group Activities from Skeletons without Individual Action Labels-
Zappardino et al. (SSAL)89.4Learning Group Activities from Skeletons without Individual Action Labels-
Shu et al.83.6CERN: Confidence-Energy Recurrent Network for Group Activity Recognition-
D. Xu et al.93.49Group Activity Recognition by Using Effective Multiple Modality Relation Representation With Temporal-Spatial Attention-
POGARS93.2Pose is all you need: The pose only group activity recognition system (POGARS)-
Joint learning (5-fusion)93.3Group Activity Recognition Using Joint Learning of Individual Action Recognition and People Grouping
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