VPN: Learning Video-Pose Embedding for Activities of Daily Living

In this paper, we focus on the spatio-temporal aspect of recognizing Activities of Daily Living (ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii) similar visual patterns varying with time... (read more)

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Results from the Paper


 Ranked #1 on Action Recognition on NTU RGB+D (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
Action Recognition NTU RGB+D VPN (RGB + Pose) Accuracy (CS) 95.5 # 1
Accuracy (CV) 98.0 # 1
Skeleton Based Action Recognition NTU RGB+D VPN Accuracy (CV) 98 # 2
Accuracy (CS) 95.5 # 2
Skeleton Based Action Recognition NTU RGB+D 120 VPN Accuracy (Cross-Subject) 86.3 # 5
Accuracy (Cross-Setup) 87.8 # 5

Methods used in the Paper


METHOD TYPE
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