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Accurate Temporal Action Proposal Generation with Relation-Aware Pyramid Network

AAAI 2020 · Video › Action recognition · approach: Fully supervised temporal action detection · 76 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace BSN with RapNet using ResNet50-C3D featuresActivityNet-v1.3 proposal generation · ActivityNet-v1.3 valAR@100: 75.61 -> 78.63Helped
replace MGG with RapNetActivityNet-v1.3 proposal generation · ActivityNet-v1.3 testAUC: 66.47 -> 70.07Helped
replace C3D MGG with C3D RapNetTHUMOS14 proposal generation · THUMOS14 test, C3DAR@50: 29.11 -> 29.72Helped
replace 2-Stream MGG with 2-Stream RapNetTHUMOS14 proposal generation · THUMOS14 test, 2-StreamAR@50: 39.93 -> 40.35Helped
increase pyramid depth from 3 to 6 (ablation)RapNet pyramid without RAM or actionness · ActivityNet-v1.3 valAUC: 64.54 -> 68.35Helped
add relation-aware modules to the temporal pyramid network (ablation)RapNet · ActivityNet-v1.3 valAUC: 68.35 -> 69.47Helped
add global context extractor and actionness prediction (ablation)relation-aware temporal pyramid network · ActivityNet-v1.3 valAUC: 69.47 -> 69.53Helped
vary anchor-box count among 6, 12, 18, and 24 (ablation)RapNet · ActivityNet-v1.3 valAUC: 68.02; 69.53; 69.24; 69.19Mixed
add TAG-based boundary adjustment (ablation)RapNet proposals · ActivityNet-v1.3 valAUC: 69.53 -> 69.71Helped
add proposal ranking after boundary adjustment (ablation)RapNet proposals with adjusted boundaries · ActivityNet-v1.3 valAUC: 69.71 -> 69.93Helped

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