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Group Activity Recognition On Volleyball

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Accuracy	Paper Title	Repository
Tamura et al.	96.0	Hunting Group Clues with Transformers for Social Group Activity Recognition	-
DIN (VGG16)	93.6	Spatio-Temporal Dynamic Inference Network for Group Activity Recognition
PoseC3D (Pose-Only)	91.3	Revisiting Skeleton-based Action Recognition
H-LSTCM	88.4	Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition	-
COMPOSER	94.69	COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality
CHASE(CTR-GCN)	92.89	CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
Zappardino et al.	91.0	Learning Group Activities from Skeletons without Individual Action Labels	-
Zappardino et al. (SSAL)	89.4	Learning Group Activities from Skeletons without Individual Action Labels	-
Shu et al.	83.6	CERN: Confidence-Energy Recurrent Network for Group Activity Recognition	-
D. Xu et al.	93.49	Group Activity Recognition by Using Effective Multiple Modality Relation Representation With Temporal-Spatial Attention	-
POGARS	93.2	Pose is all you need: The pose only group activity recognition system (POGARS)	-
Joint learning (5-fusion)	93.3	Group Activity Recognition Using Joint Learning of Individual Action Recognition and People Grouping

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Group Activity Recognition On Volleyball | SOTA | HyperAI