Human Mesh Recovery on MPI-INF-3DHP
33.33MPJPELT-fitting
Evaluation results
| Method | Links | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| LT-fittingBackbone=ResNet-152, Resolution=384x3842022.08 | 33.33 | — | — | 99.6 | 77.23 | — | — | — | |
| LMTBackbone=ResNet-152, Resolution=384x3842022.08 | 33.7 | — | — | 99.37 | 77.09 | — | — | — | |
| DiffProxytrained on specific dataset=false2026.01 | 42 | 33.6 | — | — | — | — | 45 | 51.3 | |
| LMTBackbone=ResNet-50, Resolution=224x2242022.08 | 45.87 | — | — | 96.59 | 71.57 | — | — | — | |
| Parameter regr.Backbone=ResNet-50, Resolution=224x2242022.08 | 50.2 | — | — | 97.4 | 65.6 | — | — | — | |
| SMPLest-Xtrained on specific dataset=true2026.01 | 51.6 | 33.7 | — | — | — | — | 48.8 | 67.1 | |
| HeatFormertrained on specific dataset=true2026.01 | 59.8 | 34.8 | — | — | — | — | 42.8 | 66.4 | |
| DMAPS2026.02 | 73.45 | 53.87 | — | — | — | 7.89 | — | — | |
| MuNet2026.05 | 74.3 | 56.3 | — | — | — | — | — | — | |
| MeshPose2026.05 | 74.9 | 59.5 | — | — | — | — | — | — | |
| ARTS2026.02 | 75.45 | 54.21 | — | — | — | 7.9 | — | — | |
| DiffMeshBackbone=ResNet-502023.03 | 78.9 | 54.4 | 7 | — | — | — | — | — | |
| PMCE2026.02 | 80.46 | 55.06 | — | — | — | 8 | — | — | |
| W-HMRvariant=†2023.11 | 83.2 | 59.1 | — | — | — | — | — | — | |
| W-HMRvariant=P†2023.11 | 83.3 | 58.8 | — | — | — | — | — | — | |
| MAED2023.03 | 83.6 | 56.2 | — | — | — | — | — | — | |
| MEAD2026.02 | 84.66 | 57.14 | — | — | — | 8.52 | — | — | |
| EasyMoCaptrained on specific dataset=false2026.01 | 85.5 | 47.6 | — | — | — | — | 59.6 | 93.3 | |
| W-HMRvariant=*2023.11 | 88.3 | 62 | — | — | — | — | — | — | |
| HybrIKBackbone=HRNet-W482023.04 | 91 | — | — | 87.1 | 47.3 | — | — | — | |
| STAF2023.11 | 92.4 | 58.8 | — | — | — | — | — | — | |
| HybrIKBackbone=ResNet-342023.04 | 93.3 | — | — | 86.5 | 46.9 | — | — | — | |
| PyMAF-X2026.05 | 93.5 | 56.5 | — | — | — | — | — | — | |
| GLOTBackbone=ResNet-502023.03 | 93.9 | 61.5 | 7.9 | — | — | — | — | — | |
| GLoT2026.02 | 95.76 | 62.02 | — | — | — | 8.08 | — | — | |
| MEVA2023.11 | 96.4 | 65.4 | — | — | — | — | — | — | |
| VIBE2023.11 | 96.6 | 64.6 | — | — | — | — | — | — | |
| MPS-NetBackbone=ResNet-502023.03 | 96.7 | 62.8 | 9.6 | — | — | — | — | — | |
| MPS-Net2023.11 | 96.7 | 62.8 | — | — | — | — | — | — | |
| TCMRBackbone=ResNet-502023.03 | 97.6 | 63.5 | 8.5 | — | — | — | — | — | |
| PyMAF2026.05 | 99.1 | 65.2 | — | — | — | — | — | — | |
| DecoMR2026.05 | 101 | 65.9 | — | — | — | — | — | — | |
| SPIN2026.05 | 103.7 | 66.4 | — | — | — | — | — | — | |
| VIBEBackbone=ResNet-502023.03 | 103.9 | 68.9 | 27.3 | — | — | — | — | — | |
| VIBE2026.02 | 105.08 | 69.84 | — | — | — | 28.06 | — | — | |
| SPIN2023.04 | 105.2 | — | — | 76.4 | 37.1 | — | — | — | |
| SPIN2023.11 | 105.2 | 67.5 | — | — | — | — | — | — | |
| Human3Rtrained on specific dataset=false2026.01 | 106.4 | 57 | — | — | — | — | 73.6 | 129.2 | |
| HMR2023.04 | 124.2 | — | — | 72.9 | 36.5 | — | — | — | |
| HMR2023.11 | 124.2 | 89.8 | — | — | — | — | — | — | |
| VirtualMarker2026.05 | 126.7 | 60.9 | — | — | — | — | — | — | |
| GCMR2026.05 | 132.7 | 77 | — | — | — | — | — | — | |
| U-HMRtrained on specific dataset=true2026.01 | 147.8 | 69.1 | — | — | — | — | 81.9 | 169.9 | |
| HMR2021.08 | — | 89.8 | — | — | — | — | — | — | |
| MUCtrained on specific dataset=false2026.01 | — | 37.9 | — | — | — | — | 47.9 | — | |
| ProHMR2021.08 | — | 65 | — | — | — | — | — | — | |
| SPIN2021.08 | — | 67.5 | — | — | — | — | — | — |