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SOTA
Action Detection
Action Detection On Ucf101 24
Action Detection On Ucf101 24
評価指標
Video-mAP 0.2
Video-mAP 0.5
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
Video-mAP 0.2
Video-mAP 0.5
Paper Title
Repository
HISAN (ResNet-101 + FPN)
82.30
51.47
Hierarchical Self-Attention Network for Action Localization in Videos
-
MR-TS R-CNN
-
-
Multi-region two-stream R-CNN for action detection
-
TS R-CNN
-
-
Multi-region two-stream R-CNN for action detection
-
STEP
76.6
-
STEP: Spatio-Temporal Progressive Learning for Video Action Detection
TACNet
77.5
52.9
TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection
-
Faster-RCNN + two-stream I3D conv
-
59.9
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
HIT
88.8
74.3
Holistic Interaction Transformer Network for Action Detection
HISAN (VGG-16)
80.42
49.50
Hierarchical Self-Attention Network for Action Localization in Videos
-
YOWO
75.8
48.8
You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
-
MOC
81.8
53.9
Actions as Moving Points
T-CNN
47.1
-
Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos
YOWO + LFB
78.6
53.1
You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
-
Two-in-one
75.48
48.31
Dance with Flow: Two-in-One Stream Action Detection
Two-in-one Two Stream
78.48
50.30
Dance with Flow: Two-in-One Stream Action Detection
DTS
-
54
Finding Action Tubes with a Sparse-to-Dense Framework
-
E2E-SSL (I3D)
-
72.1
End-to-End Semi-Supervised Learning for Video Action Detection
Stable Mean Teacher (I3D)
-
76.3
Stable Mean Teacher for Semi-supervised Video Action Detection
-
STAR/L
88.0
71.8
End-to-End Spatio-Temporal Action Localisation with Video Transformers
-
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