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Spatio-Temporal Naive-Bayes Nearest-Neighbor (ST-NBNN) for Skeleton-Based Action Recognition

CVPR 2017 · Video › Action recognition · approach: Skeleton-based action recognition · 138 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add learned spatio-temporal bilinear weights to NBNNNBNN · MSR-Action3D averageaccuracy: 91.4 -> 94.8Helped
Add learned spatio-temporal bilinear weights to NBNNNBNN · UTKinectaccuracy: 95.5 -> 98.0Helped
Add learned spatio-temporal bilinear weights to NBNNNBNN · Berkeley MHADaccuracy: 88.0 -> 100.0Helped
Use 15 temporal stages instead of no fixed stage setting (ablation)NBNN · MSR-Action3D averageaccuracy: 91.4 -> 91.7Helped
Use 15 temporal stages instead of no fixed stage setting (ablation)NBNN · UTKinectaccuracy: 95.5 -> 95.5No clear effect
Learn a separate linear-SVM weight for every distance-matrix element (ablation)NBNN · MSR-Action3Daccuracy: AS1: 85.8 -> 90.6; AS2: 92.0 -> 90.3; AS3: 96.4 -> 96.4Mixed
Learn a separate linear-SVM weight for every distance-matrix element (ablation)NBNN · UTKinectaccuracy: 95.5 -> 94.0Hurt
Learn a separate linear-SVM weight for every distance-matrix element (ablation)NBNN · Berkeley MHADaccuracy: 88.0 -> 100.0Helped
Increase the number of temporal stages beyond 11 (ablation)ST-NBNN · MSR-Action3DaccuracyNo clear effect
Use only 3 poses per stage when the stage count exceeds 11 (ablation)ST-NBNN · MSR-Action3DaccuracyHelped
Add random coordinate noise to an increasing proportion of joints (ablation)ST-NBNN · Berkeley MHADaccuracyMixed
Constrain temporal weights to be nonnegative and sum to the stage count (ablation)ST-NBNN · 3D action recognitionaccuracyHelped

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