Papers › Self-Attentive 3D Human Pose and Shape Estimation from Videos

Self-Attentive 3D Human Pose and Shape Estimation from Videos

26 Mar 2021arXiv:2103.14182archive 2025-07-28

Yun-Chun Chen, Marco Piccirilli, Robinson Piramuthu, Ming-Hsuan Yang

We consider the task of estimating 3D human pose and shape from videos. While existing frame-based approaches have made significant progress, these methods are independently applied to each image, thereby often leading to inconsistent predictions. In this work, we present a video-based learning algorithm for 3D human pose and shape estimation. The key insights of our method are two-fold. First, to address the inconsistent temporal prediction issue, we exploit temporal information in videos and propose a self-attention module that jointly considers short-range and long-range dependencies across frames, resulting in temporally coherent estimations. Second, we model human motion with a forecasting module that allows the transition between adjacent frames to be smooth. We evaluate our method on the 3DPW, MPI-INF-3DHP, and Human3.6M datasets. Extensive experimental results show that our algorithm performs favorably against the state-of-the-art methods.

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Tasks

3D Human Pose Estimation3D human pose and shape estimation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Human Pose Estimation 3DPW Self-Attentive Acceleration Error 77.9 #50 of 119 Archive leaderboard report
3D Human Pose Estimation 3DPW Self-Attentive MPJPE 85.8 #50 of 119 Archive leaderboard report
3D Human Pose Estimation 3DPW Self-Attentive MPVPE 100.6 #50 of 119 Archive leaderboard report
3D Human Pose Estimation 3DPW Self-Attentive PA-MPJPE 50.4 #50 of 119 Archive leaderboard report
3D Human Pose Estimation MPI-INF-3DHP Self-Attentive MPJPE 94.3 #54 of 108 Archive leaderboard report
3D Human Pose Estimation MPI-INF-3DHP Self-Attentive PA-MPJPE 60.7 #54 of 108 Archive leaderboard report
3D Human Pose Estimation MPI-INF-3DHP Self-Attentive PCK 90.1 #54 of 108 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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