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홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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Skeleton Based Action Recognition On Kinetics

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
Accuracy
Paper TitleRepository
ProtoGCN51.9Revealing Key Details to See Differences: A Novel Prototypical Perspective for Skeleton-based Action Recognition-
ST-TR-agcn37.4Skeleton-based Action Recognition via Spatial and Temporal Transformer Networks-
ST-GCN (2-stream)34.4Continual Spatio-Temporal Graph Convolutional Networks-
CGCN37.5Unifying Graph Embedding Features with Graph Convolutional Networks for Skeleton-based Action Recognition-
CoST-GCN* (1-stream)30.2Continual Spatio-Temporal Graph Convolutional Networks-
Structured Keypoint Pooling (PPNv2 skeletons+objects)52.3Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling-
CoAGCN* (1-stream)23.3Continual Spatio-Temporal Graph Convolutional Networks-
SLnL-rFA36.6Skeleton-Based Action Recognition with Synchronous Local and Non-local Spatio-temporal Learning and Frequency Attention-
ST-GR33.6Spatiotemporal graph routing for skeleton-based action recognition-
DualHead-Net38.4Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition-
Dynamic GCN37.9Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition-
CoST-GCN* (2-stream)32.2Continual Spatio-Temporal Graph Convolutional Networks-
MS-G3D38.0Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition-
JB-AAGCN37.4Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks-
AS-GCN34.8Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition-
DGNN36.9Skeleton-Based Action Recognition With Directed Graph Neural Networks-
CoS-TR* (1-stream)27.4Continual Spatio-Temporal Graph Convolutional Networks-
CoAGCN (1-stream)33Continual Spatio-Temporal Graph Convolutional Networks-
2s-AGCN+TEM38.6Temporal Extension Module for Skeleton-Based Action Recognition-
HD-GCN40.9Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action Recognition-
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