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Research map / Video / Action recognition

Multi-Granularity Generator for Temporal Action Proposal

CVPR 2019 · Video › Action recognition · approach: Weakly supervised temporal action localization · 227 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add position embedding to video features (ablation)MGG · ActivityNet-1.3 valAUC: 65.59 -> 66.43Helped
Add bilinear matching between BaseNet convolutional representations (ablation)MGG · ActivityNet-1.3 valAUC: 65.88 -> 66.43Helped
Add the U-shape architecture in SPP (ablation)MGG · ActivityNet-1.3 valAUC: 65.02 -> 66.43Helped
Add FAP and TBA to SPP proposals (ablation)MGG · ActivityNet-1.3 valAUC: 64.31 -> 66.43Helped
Add SPP and TBA to FAP proposals (ablation)MGG · ActivityNet-1.3 valAUC: 59.91 -> 66.43Helped
Add the U-shape architecture (ablation)MGG · ActivityNet-1.3 val, AN=100, tIoU=0.75, proposals 0-5srecall: 0.15 -> 0.21Helped
Add TBA Stage 1 boundary adjustment (ablation)MGG-F, end-to-end training · ActivityNet-1.3 valAUC: 64.31 -> 65.54Helped
Add TBA Stage 2 middle-probability grouping adjustment (ablation)MGG-F with Stage 1, end-to-end training · ActivityNet-1.3 valAUC: 65.54 -> 66.43Helped
Train SPP and FAP jointly end-to-end rather than stagewise (ablation)MGG with both TBA stages · ActivityNet-1.3 valAUC: 66.28 -> 66.43Helped
Use coarse segment proposals alongside fine frame actionness (ablation)MGG · ActivityNet-1.3 valAUC: 64.31 -> 66.43Helped

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