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Mar, 2023
多人姿势预测的轨迹感知身体交互变换器
Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting
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Xiaogang Peng, Siyuan Mao, Zizhao Wu
TL;DR
本文提出了一种称之为TBIFormer的新型多人姿态预测框架,利用社交身体相互作用自我关注机制和轨迹感知相对位置编码来高效地建模身体部位间的交互影响,实验结果表明,在短时和长时预测上,该方法在CMU-Mocap、MuPoTS-3D和合成数据集方面,都显著优于现有的其他方法。
Abstract
multi-person pose forecasting
remains a challenging problem, especially in modeling fine-grained human
body interaction
in complex crowd scenarios. Existing methods typically represent the whole pose sequence as
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