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Research map / Video / Action recognition

Temporal Pyramid Network for Action Recognition

CVPR 2020 · Video › Action recognition · approach: Spatiotemporal CNNs for action recognition · 469 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add TPN to I3D-50I3D-50 · Kinetics-400 validation, 8×8 framesTop-1 accuracy: 74.9 -> 76.1 (+1.2)Helped
Add TPN to I3D-50I3D-50 · Kinetics-400 validation, 32×2 framesTop-1 accuracy: 75.7 -> 77.7 (+2.0)Helped
Add TPN to TSN-50TSN-50 · Kinetics-400 validation, 8 segmentsTop-1 accuracy: 69.9 -> 73.5Helped
Add TPN to TSM-50TSM-50 · Something-Something V1 validationTop-1 accuracy: 45.6 -> 49.0Helped
Add TPN to TSM-50TSM-50 · Something-Something V2 validationTop-1 accuracy: 59.1 -> 62.0Helped
Add TPN to TSNTSN · Epic-Kitchen validationVERB@1: 48.2 -> 61.1Helped
Use res4 and res5 as feature sources rather than shallow res2/res3 stages (ablation)TPN on I3D-50 · Kinetics-400 validationTop-1 accuracy: 74.6 -> 76.1Helped
Add spatial convolutions to the auxiliary-head variant (ablation)TPN on I3D-50 · Kinetics-400 validationTop-1 accuracy: 74.6 -> 75.2Helped
Add temporal rate modulation after spatial modulation (ablation)TPN on I3D-50 · Kinetics-400 validationTop-1 accuracy: 75.2 -> 75.4Helped
Add information flow to the modulated TPN (ablation)TPN on I3D-50 · Kinetics-400 validationTop-1 accuracy: 75.4 -> 76.1Helped
Add the auxiliary classification head (ablation)TPN on I3D-50 · Kinetics-400 validationTop-1 accuracy: 75.9 -> 76.1Hurt
Use parallel information flow instead of isolation flow (ablation)TPN on I3D-50 · Kinetics-400 validationTop-1 accuracy: 75.4 -> 76.1Helped

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