Multi-modal Shape Matching on FAUST (test) benchmark leaderboard · SOTA2 Research

Multi-modal Shape Matching on FAUST (test)

0.018Mean Geodesic Error (Triangle Meshes)Ours (Hyper-Network Neural Functional Maps)

Evaluation Results

Method
Ours (Hyper-Network Neural Functional Maps)2026.06	0.018	0.022
SSMSM2026.06	0.02	0.024
3D-CODED2026.06	0.025	0.025
TransMatch2026.06	0.027	0.027
DFR2026.06	0.03	0.03
Ours (Hyper-Network Neural Functional Maps)2026.06	0.032	0.037
DiffFMaps2026.06	0.036	0.036
DFR2026.06	0.04	0.04
NIE2026.06	0.055	0.055
SSMSM2026.06	0.072	0.085
NIE2026.06	0.087	0.087
DCP2026.06	0.111	0.111
DCP2026.06	0.112	0.112
DiffFMaps2026.06	0.12	0.12
TransMatch2026.06	0.183	0.183
CorrNet3D2026.06	0.265	0.265
3D-CODED2026.06	0.33	0.33
CorrNet3D2026.06	0.362	0.362