Table 3 Comparison of the proposed method with previous methods on the PKU-MMD dataset (mAP@tIoU = 0.5)

From: Localization and recognition of human action in 3D using transformers

Method

Cross-view

Cross-subject

JCRRNN77

53.3

32.5

TAP-B-M78

48.6

35.2

Beyond-Joints31

91.1

81.1

Cui et al.30

93.3

83.5

LocATe

94.6

93.2

  1. LocATe attains state-of-the-art performance and stands out by surpassing the previous methods by almost 10% in the context of cross-subject evaluation. PKU-MMD Peking University Multi-Modal Dataset, mAP mean Average Precision, tIoU threshold IoU.
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