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A flexible model for training action localization with varying levels of supervision

NeurIPS 2018 · Video › Action recognition · approach: Weakly supervised temporal action localization · 25 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use temporal-point labels instead of temporal bounds (ablation)Our method · DALYmAP@0.2: 31.5 -> 26.7Hurt
Use temporal-point labels instead of temporal bounds (ablation)Our method · UCF101-24mAP@0.2: 47.3 -> 45.5Hurt
Add a few fully supervised videos to video-level-labeled training videosOur method · DALYmAP@0.2: 7.6 -> 18.2Helped
Use temporal-point labels for the weakly labeled portion when mixing supervisionOur method · DALYmAP@0.2: nullHelped
Add spatial bounding-box supervision to temporal bounds (ablation)Our method · DALYmAP@0.2: +1.0%Helped
Add three sparse bounding boxes to temporal bounds (ablation)Our method · UCF101-24mAP@0.2: 47.3 -> 74.5Helped
Add three sparse bounding boxes to temporal bounds (ablation)Our method · UCF101-24mAP@0.5: 20.1 -> 43.2Helped
Use the cited method's tracks instead of generic person-detector tracks (ablation)Our method · UCF101-24 video-level supervisionmAP@0.2: 43.9 -> 53.1Helped
Add one bounding box to temporal bounds (ablation)Our method · UCF101-24mAP@0.2: 47.3 -> 70.6Helped

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