Despite the significant improvement in the performance of monocular pose estimation
approaches and their ability to generalize to unseen environments, multi-view approaches …

Recently, stacked hourglass network has shown outstanding performance in human pose
estimation. However, repeated bottom-up and top-down stride convolution operations in …

At present, human body moving target detection and recognition algorithms based on deep
learning have made breakthrough progress. However, in some applications with high real …

A 3D martial arts gestures estimation method is proposed, for it is difficult to accurately
describe the gestures, which is caused by the high degree of freedom and high similarity of …

Human pose estimation has attracted enormous interest in the field of human action
recognition. When the human pose is complex (such as pose distortion, pose reversal, etc.) …

This work introduces a novel convolutional feature for the task of human pose estimation,
which is a framework of fusing a convolutional neural network into a multi-level graph …

This paper proposes a novel deep neural network model for solving the spatio-temporal-
action-detection problem, by localizing all multiple-action regions and classifying the …

Aimingattheproblemthatthetraditionalvisual… artificialmarkofthetargetinthescene, arelativeposemeasurementmethodispropos…
designedbasedonfeaturematching. Therelativeposemeasurementdoesnotneedt …

This chapter proposes the deep neural networks to enhance visual teleoperation
considering human–robot posture consistence. Firstly, the teacher–student network …