Global human motion forecasting is important in many fields, which is the combination of global human trajectory prediction and local human pose prediction. Visual and social information are often used to boost model performance, however, they may consume too much computational resource. In this paper, we establish a simple but effective baseline for single human motion forecasting without visual and social information, equipped with useful training tricks. Our method "futuremotion_ICCV21" outperforms existing methods by a large margin on SoMoF benchmark. We hope our work provide new ideas for future research.
翻译:全球人类运动预测在许多领域都很重要,即全球人类轨迹预测和当地人类姿势预测相结合。视觉和社会信息常常被用来提高模型性能,然而,它们消耗的计算资源可能过多。在本文件中,我们为没有视觉和社会信息的单一人类运动预测建立了简单而有效的基线,并配备了有用的培训技巧。我们的“未来-ICCV21”方法大大优于SoMoF基准的现有方法。我们希望我们的工作为未来的研究提供新的想法。