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SOTA
动作分割
Action Segmentation On Breakfast 1
Action Segmentation On Breakfast 1
评估指标
Acc
Average F1
Edit
F1@10%
F1@25%
F1@50%
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Acc
Average F1
Edit
F1@10%
F1@25%
F1@50%
Paper Title
Repository
AdaFocus (newly extracted I3D-features, LT-Context model)
78.0
76.2
78.3
82.1
79.0
67.5
Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition
-
ASQuery
77.9
74.6
78.4
80.7
76.5
66.5
ASQuery: A Query-based Model for Action Segmentation
-
SF-TMN(ASFormer)
77.0
71.6
77.0
78.7
74.0
62.2
SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition
-
BaFormer
76.6
72.4
77.3
79.2
74.9
63.2
Efficient Temporal Action Segmentation via Boundary-aware Query Voting
DiffAct
76.4
73.6
78.4
80.3
75.9
64.6
Diffusion Action Segmentation
FACT (efficient hybrid of convolution and transformer model)
76.2
74.7
79.7
81.4
76.5
66.2
FACT: Frame-Action Cross-Attention Temporal Modeling for Efficient Action Segmentation
-
C2F-TCN
76.0
66.2
69.6
72.2
68.7
57.6
Coarse to Fine Multi-Resolution Temporal Convolutional Network
ASPnet
75.9
70.6
76.3
78.1
72.9
60.8
ASPnet: Action Segmentation With Shared-Private Representation of Multiple Data Sources
-
BIT
75.5
73.7
79.0
80.6
75.8
64.7
BIT: Bi-Level Temporal Modeling for Efficient Supervised Action Segmentation
-
EUT
75
69.3
74.6
76.2
71.8
59.8
Do we really need temporal convolutions in action segmentation?
CETNet
74.9
71.8
77.8
79.3
74.3
61.9
Cross-Enhancement Transformer for Action Segmentation
LTContext
74.2
70.1
77.0
77.6
72.6
60.1
How Much Temporal Long-Term Context is Needed for Action Segmentation?
ASFormer
73.5
68.0
75.0
76.0
70.6
57.4
ASFormer: Transformer for Action Segmentation
DPRN
71.7
67.9
75.1
75.6
70.5
57.6
Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction
-
DA
71.0
66.4
73.6
74.2
68.6
56.5
Action Segmentation with Mixed Temporal Domain Adaptation
-
G2L(SSTDA)
70.8
66.9
74.5
76.3
69.9
54.6
Global2Local: Efficient Structure Search for Video Action Segmentation
RF++-SSTDA
70.8
-
-
-
-
-
RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks
DS-TCN
70.75
59.6
69.02
67.70
62.05
49.18
Depthwise Separable Temporal Convolutional Network for Action Segmentation
-
BCN
70.4
63.1
66.2
68.7
65.5
55.0
Boundary-Aware Cascade Networks for Temporal Action Segmentation
-
SSTDA
70.2
66.4
73.7
75.0
69.1
55.2
Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
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Action Segmentation On Breakfast 1 | SOTA | HyperAI超神经