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Models/ASRF

ASRF

Reported on 32 benchmarks across 2 tasks · 1 paper · 14 SOTA

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

Computer Vision32 results

Action Localizationon50 Salads
Acc· 2020-07-14
84.5
best: 91.4 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Localizationon50 Salads
Edit· 2020-07-14
79.3
best: 89.1 (Semantic2Graph)
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Localizationon50 Salads
F1@10%· 2020-07-14
84.9
best: 92.7 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Localizationon50 Salads
F1@25%· 2020-07-14
83.5
best: 91.6 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Localizationon50 Salads
F1@50%· 2020-07-14
77.3
best: 88.5 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonGTEA
F1@50%· 2020-07-14
79.8
best: 91.3 (Semantic2Graph)
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonBreakfast
F1@50%· 2020-07-14
56.1
best: 67.5 (AdaFocus (newly extracted I3D-features, LT-Context model))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Segmentationon50 Salads
Acc· 2020-07-14
84.5
best: 91.4 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Segmentationon50 Salads
Edit· 2020-07-14
79.3
best: 89.1 (Semantic2Graph)
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Segmentationon50 Salads
F1@10%· 2020-07-14
84.9
best: 92.7 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Segmentationon50 Salads
F1@25%· 2020-07-14
83.5
best: 91.6 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action Segmentationon50 Salads
F1@50%· 2020-07-14
77.3
best: 88.5 (Br-Prompt+ASPnet (RGB, flow, accelerometer))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonGTEA
F1@50%· 2020-07-14
79.8
best: 91.3 (Semantic2Graph)
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonBreakfast
F1@50%· 2020-07-14
56.1
best: 67.5 (AdaFocus (newly extracted I3D-features, LT-Context model))
SOTA
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonGTEA
Acc· 2020-07-14
77.3
best: 89.8 (Semantic2Graph)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonGTEA
Edit· 2020-07-14
83.7
best: 93.5 (FACT)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonGTEA
F1@10%· 2020-07-14
89.4
best: 96.1 (FACT)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonGTEA
F1@25%· 2020-07-14
87.8
best: 95.6 (FACT)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonBreakfast
Acc· 2020-07-14
67.6
best: 78 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonBreakfast
Average F1· 2020-07-14
66.4
best: 76.2 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonBreakfast
Edit· 2020-07-14
72.4
best: 79.7 (FACT (efficient hybrid of convolution and transformer model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonBreakfast
F1@10%· 2020-07-14
74.3
best: 82.1 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action LocalizationonBreakfast
F1@25%· 2020-07-14
68.9
best: 79 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonGTEA
Acc· 2020-07-14
77.3
best: 89.8 (Semantic2Graph)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonGTEA
Edit· 2020-07-14
83.7
best: 93.5 (FACT)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonGTEA
F1@10%· 2020-07-14
89.4
best: 96.1 (FACT)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonGTEA
F1@25%· 2020-07-14
87.8
best: 95.6 (FACT)
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonBreakfast
Acc· 2020-07-14
67.6
best: 78 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonBreakfast
Average F1· 2020-07-14
66.4
best: 76.2 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonBreakfast
Edit· 2020-07-14
72.4
best: 79.7 (FACT (efficient hybrid of convolution and transformer model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonBreakfast
F1@10%· 2020-07-14
74.3
best: 82.1 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866
Action SegmentationonBreakfast
F1@25%· 2020-07-14
68.9
best: 79 (AdaFocus (newly extracted I3D-features, LT-Context model))
Alleviating Over-segmentation Errors by Detecting Action Boundaries arXiv:2007.06866