3D Human Pose Estimation on Radar Dataset Participant P1 (test)
3.97P-MPJPE (0°)RPP-Gauss.-Gauss.-Cov.
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| RPP-Gauss.-Gauss.-Cov.Latent Prior=Gauss., Log-likelihood=Gauss., Covariance Type=Full covariance2025.08 | 3.97 | 5.074 | 5.918 | 4.987 | |
| RPP-Laplace-Gauss.Latent Prior=Laplace, Log-likelihood=Gauss.2025.08 | 4.237 | 5.416 | 5.942 | 5.198 | |
| Engel et al.Input Modality=Pointcloud-based2025.08 | 4.521 | 5.625 | 7.762 | 5.969 | |
| Ho et al.2025.08 | 4.524 | 5.559 | 6.315 | 5.466 | |
| RPP-Gauss.-Gauss.Latent Prior=Gauss., Log-likelihood=Gauss.2025.08 | 4.764 | 5.29 | 5.793 | 5.282 | |
| RPP-Laplace-LaplaceLatent Prior=Laplace, Log-likelihood=Laplace2025.08 | 5.116 | 5.807 | 6.287 | 5.737 | |
| RPP-Gauss.-LaplaceLatent Prior=Gauss., Log-likelihood=Laplace2025.08 | 5.131 | 6.155 | 6.841 | 6.042 | |
| RPP-Normalizing-FlowsLatent Prior=Normalizing-Flows2025.08 | 5.168 | 6.424 | 6.725 | 6.106 | |
| Evidential Regression2025.08 | 9.576 | 10.394 | 10.709 | 10.226 |