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Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization

CVPR 2019 · Video › Action recognition · approach: Weakly supervised temporal action localization · 267 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use the proposed multi-branch network and hard-negative miningweakly supervised temporal action localization with I3D features · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 39.8 -> 40.9Helped
use the proposed multi-branch network and hard-negative miningweakly supervised temporal action localization with UntrimmedNet features · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 33.7 -> 37.4Helped
use the proposed methodweakly supervised temporal action localization with I3D features · ActivityNet1.2 validationaverage mAP (IoU 0.5:0.05:0.95): 18.0 -> 22.4Helped
use the proposed methodweakly supervised temporal action localization with I3D features · ActivityNet1.3 testaverage mAP (IoU 0.5:0.05:0.95): 20.1 -> 23.1Helped
add hard-negative videos (ablation)single-branch model with MIL loss · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 28.8 -> 32.7Helped
use multiple classification branches and Lsum instead of a single branch with MIL loss (ablation)weakly supervised temporal action localization · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 28.8 -> 34.8Helped
add diversity loss (ablation)multiple-branch model trained with MIL loss and hard negatives · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 34.7 -> 35.6Helped
add norm regularization (ablation)multiple-branch model with diversity loss and hard negatives · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 35.6 -> 37.4Helped
add the temporal attention module (ablation)multiple-branch full model with hard negatives · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 36.3 -> 37.4Helped
vary the hard-negative selection ratio among 15%, 20%, 25%, and 30% (ablation)single-branch model with hard-negative mining · THUMOS’14 testaverage mAP (IoU 0.1:0.5): 32.4, 33.3, 32.7, 32.8No clear effect

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