Papers › On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation
On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation
Soumava Kumar Roy, Leonardo Citraro, Sina Honari, Pascal Fua
Supervised approaches to 3D pose estimation from single images are remarkably effective when labeled data is abundant. However, as the acquisition of ground-truth 3D labels is labor intensive and time consuming, recent attention has shifted towards semi- and weakly-supervised learning. Generating an effective form of supervision with little annotations still poses major challenge in crowded scenes. In this paper we propose to impose multi-view geometrical constraints by means of a weighted differentiable triangulation and use it as a form of self-supervision when no labels are available. We therefore train a 2D pose estimator in such a way that its predictions correspond to the re-projection of the triangulated 3D pose and train an auxiliary network on them to produce the final 3D poses. We complement the triangulation with a weighting mechanism that alleviates the impact of noisy predictions caused by self-occlusion or occlusion from other subjects. We demonstrate the effectiveness of our semi-supervised approach on Human3.6M and MPI-INF-3DHP datasets, as well as on a new multi-view multi-person dataset that features occlusion.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Weakly-supervised 3D Human Pose Estimation | Human3.6M | Triangulation | Average MPJPE (mm) | 64.7 | #16 of 33 | Archive leaderboard | report |
| Weakly-supervised 3D Human Pose Estimation | Human3.6M | Triangulation | PA-MPJPE | 52.1 | #16 of 33 | Archive leaderboard | report |
| Weakly-supervised 3D Human Pose Estimation | MPI-INF-3DHP | Triangulation | MPJPE | 118.4 | #2 of 3 | Archive leaderboard | report |
| Weakly-supervised 3D Human Pose Estimation | MPI-INF-3DHP | Triangulation | PCK | 73.4 | #2 of 3 | 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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