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Distilling Vision-Language Pre-Training To Collaborate With Weakly-Supervised Temporal Action Localization

CVPR 2023 · 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
distill complementary foreground and background pseudo-labels with alternating B and F steps (ablation)CBP–VLP collaboration · THUMOS14mAP@IoU 0.3-0.7 average: 37.8 -> 40.8Helped
distill foreground pseudo-labels from vanilla VLP only (ablation)CBP–VLP collaboration · THUMOS14mAP@IoU 0.3-0.7 average: 27.7 -> 40.8Hurt
add confident foreground-background knowledge distillation (ablation)CBP–VLP collaboration · THUMOS14mAP@IoU 0.3-0.7 average: 30.9 -> 40.8Helped
add foreground-background contrastive loss (ablation)CBP–VLP collaboration · THUMOS14mAP@IoU 0.3-0.7 average: 36.0 -> 40.8Helped
use the distillation-collaboration framework rather than DELUWTAL · THUMOS14mAP@IoU 0.3-0.7 average: 37.4 -> 40.8Helped
use the distillation-collaboration framework rather than DELUWTAL · ActivityNet1.2average mAP: 26.9 -> 29.6Helped
add CLIP features by averaging or concatenating them with I3D featuresCO2-Net and DELU · THUMOS14mAP@IoU 0.3-0.7 average: CO2-Net: 35.7 -> 32.2; DELU: 37.4 -> 35.8Mixed
apply the framework using UM as the CBP branch (ablation)UM · THUMOS14mAP@IoU 0.3: 49.0 -> 53.9Helped
apply the framework using CO2-Net as the CBP branch (ablation)CO2-Net · THUMOS14mAP@IoU 0.3: 54.5 -> 56.2Helped

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