Papers › Learning Temporal 3D Human Pose Estimation with Pseudo-Labels
Learning Temporal 3D Human Pose Estimation with Pseudo-Labels
Arij Bouazizi, Ulrich Kressel, Vasileios Belagiannis
We present a simple, yet effective, approach for self-supervised 3D human pose estimation. Unlike the prior work, we explore the temporal information next to the multi-view self-supervision. During training, we rely on triangulating 2D body pose estimates of a multiple-view camera system. A temporal convolutional neural network is trained with the generated 3D ground-truth and the geometric multi-view consistency loss, imposing geometrical constraints on the predicted 3D body skeleton. During inference, our model receives a sequence of 2D body pose estimates from a single-view to predict the 3D body pose for each of them. An extensive evaluation shows that our method achieves state-of-the-art performance in the Human3.6M and MPI-INF-3DHP benchmarks. Our code and models are publicly available at \url{https://github.com/vru2020/TM_HPE/}.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Human Pose Estimation | Human3.6M | Multi-view Temporal self-supervised | Average MPJPE (mm) | 50.6 | #66 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | Multi-view Temporal self-supervised | Multi-View or Monocular | Multi-View | #66 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | Multi-view Temporal self-supervised | Using 2D ground-truth joints | No | #66 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | MPI-INF-3DHP | Multi-view Temporal self-supervised | AUC | 50.1 | #50 of 108 | Archive leaderboard | report |
| 3D Human Pose Estimation | MPI-INF-3DHP | Multi-view Temporal self-supervised | MPJPE | 93.0 | #50 of 108 | Archive leaderboard | report |
| 3D Human Pose Estimation | MPI-INF-3DHP | Multi-view Temporal self-supervised | PCK | 81.0 | #50 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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