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Models/MS-TCN++(sh)

MS-TCN++(sh)

Reported on 20 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision20 results

Action Localizationon50 Salads
Acc· 2020-06-16
82.2
best: 91.4 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Localizationon50 Salads
Edit· 2020-06-16
70.7
best: 89.1 (Semantic2Graph)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Localizationon50 Salads
F1@10%· 2020-06-16
78.7
best: 92.7 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Localizationon50 Salads
F1@25%· 2020-06-16
76.6
best: 91.6 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Localizationon50 Salads
F1@50%· 2020-06-16
68.3
best: 88.5 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action LocalizationonGTEA
Acc· 2020-06-16
79.7
best: 89.8 (Semantic2Graph)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action LocalizationonGTEA
Edit· 2020-06-16
83
best: 93.5 (FACT)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action LocalizationonGTEA
F1@10%· 2020-06-16
88.2
best: 96.1 (FACT)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action LocalizationonGTEA
F1@25%· 2020-06-16
86.2
best: 95.6 (FACT)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action LocalizationonGTEA
F1@50%· 2020-06-16
75.9
best: 91.3 (Semantic2Graph)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Segmentationon50 Salads
Acc· 2020-06-16
82.2
best: 91.4 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Segmentationon50 Salads
Edit· 2020-06-16
70.7
best: 89.1 (Semantic2Graph)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Segmentationon50 Salads
F1@10%· 2020-06-16
78.7
best: 92.7 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Segmentationon50 Salads
F1@25%· 2020-06-16
76.6
best: 91.6 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action Segmentationon50 Salads
F1@50%· 2020-06-16
68.3
best: 88.5 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action SegmentationonGTEA
Acc· 2020-06-16
79.7
best: 89.8 (Semantic2Graph)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action SegmentationonGTEA
Edit· 2020-06-16
83
best: 93.5 (FACT)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action SegmentationonGTEA
F1@10%· 2020-06-16
88.2
best: 96.1 (FACT)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action SegmentationonGTEA
F1@25%· 2020-06-16
86.2
best: 95.6 (FACT)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220
Action SegmentationonGTEA
F1@50%· 2020-06-16
75.9
best: 91.3 (Semantic2Graph)
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation arXiv:2006.09220