Despite the recent success of single image-based 3D human pose and shape
estimation methods, recovering temporally consistent and smooth 3D human motion
from a video is still challenging. Several video-based methods have been
proposed; however, they fail to resolve the single image-based methods'
temporal inconsistency issue due to a strong dependency on a static feature of
the current frame. In this regard, we present a temporally consistent mesh
recovery system (TCMR). It effectively focuses on the past and future frames'
temporal information without being dominated by the current static feature. Our
TCMR significantly outperforms previous video-based methods in temporal
consistency with better per-frame 3D pose and shape accuracy. We also release
the codes. For the demo video, see this https URL For the codes,
see this https URL

该研究提出了一种基于视频的 3D 人体运动重建系统，该系统有效聚焦于过去和未来帧的时间信息，从而更好地解决了单张图像方法的时间不一致性问题。通过在帧间进行时间一致性的处理，该系统达到了更好的运动姿态和形状精度。