Papers › RapidPoseTriangulation: Multi-view Multi-person Whole-body Human Pose Triangulation in...
RapidPoseTriangulation: Multi-view Multi-person Whole-body Human Pose Triangulation in a Millisecond
Daniel Bermuth, Alexander Poeppel, Wolfgang Reif
The integration of multi-view imaging and pose estimation represents a significant advance in computer vision applications, offering new possibilities for understanding human movement and interactions. This work presents a new algorithm that improves multi-view multi-person pose estimation, focusing on fast triangulation speeds and good generalization capabilities. The approach extends to whole-body pose estimation, capturing details from facial expressions to finger movements across multiple individuals and viewpoints. Adaptability to different settings is demonstrated through strong performance across unseen datasets and configurations. To support further progress in this field, all of this work is publicly accessible.
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 Multi-Person Pose Estimation | Panoptic | RapidPoseTriangulation (without training) | Average MPJPE (mm) | 30.5 | #9 of 20 | Archive leaderboard | report |
| 3D Multi-Person Pose Estimation | Shelf | RapidPoseTriangulation (with corrected labels) | MPJPE | 47.5 | #1 of 27 | Archive leaderboard | report |
| 3D Multi-Person Pose Estimation | Shelf | RapidPoseTriangulation (with corrected labels) | PCP3D | 100 | #1 of 27 | 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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