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3D Human Pose and Shape Estimation on AGORA (test)

68NMJE (All)AiOS
57.66127.455197.25267.045Nov 21, 2022Feb 10, 2023May 3, 2023Jul 24, 2023Oct 14, 2023Jan 4, 2024Mar 26, 2024

Evaluation results

MethodLinks
AiOSMethod categorization=One-stage, Detection score threshold=0.52024.036861.2——57.5————63.9————0.94—0.980.9
AiOSMethod categorization=One-stage, Detection score threshold=0.32024.0370.163.4——60.9————67.3————0.96—0.970.95
NIKIMethod categorization=Top-down, Fine-tuned on AGORA training set=true2024.037470.2——63.9————67.3————0.91—0.920.9
PLIKS (HR48)Backbone=HRNet-W482022.1176.171.6——67.3————71.5————0.94———
PLIKSMethod categorization=Top-down, Fine-tuned on AGORA training set=true2024.0376.171.6——67.3————71.5————0.94—0.950.93
PLIKS‡Training Mode=trained on all 2D and 3D datasets, Focal length estimation=CamCalib2022.1179.674.9——70.4————74.8————0.94———
BoPRProjection type=weak perspective, Fine-tuned on AGORA=true2023.0379.9——————————————74.5——
CLIFFProjection type=weak perspective, Fine-tuned on AGORA=true2023.0381——————————————76——
PLIKSTraining Mode=fine-tuned on AGORA2022.1181.576.8——72.2————76.6————0.94———
ProPoseMethod categorization=Top-down, Fine-tuned on AGORA training set=true2024.0382.778.8——70.9————74.4————0.9—0.910.89
PLIKS†Training Mode=trained on all 2D and 3D datasets2022.118378.3——73.6————78————0.94———
HybrIKMethod categorization=Top-down, Fine-tuned on AGORA training set=true2024.0384.681.2——73.9————77————0.91—0.920.9
CLIFF2022.118983.5——76————81————0.91———
CLIFFMethod categorization=Top-down, Fine-tuned on AGORA training set=true2024.038983.5——76————81————0.91—0.960.87
Hand4WholeProjection type=weak perspective, Fine-tuned on AGORA=true2023.0389.8——————————————84.8——
H4W2022.1195.590.2——84.8————89.8————0.94———
H4WMethod categorization=Top-down, Fine-tuned on AGORA training set=true2024.0395.590.2——84.8————89.8————0.94—0.960.93
BEVProjection type=weak perspective, Fine-tuned on AGORA=true2023.03105.3——————————————100.7——
ROMPProjection type=weak perspective, Fine-tuned on AGORA=true2023.03108.1——————————————103.4——
BEV2022.11113.2108.3——100.7————105.3————0.93———
BEVMethod categorization=One-stage, Fine-tuned on AGORA training set=true2024.03113.2108.3——100.7————105.3————0.93—0.960.9
HumanWildfinetuned on AGORA training set=true2024.03115.7120.573.772.3112.168.53746.747107.667.238.541.241.4————
SPEC2022.11118.8113.6——103.4————108.1————0.84———
ROMPMethod categorization=One-stage, Fine-tuned on AGORA training set=true2024.03118.8113.6——103.4————108.1————0.91—0.950.88
OSXtrained on AGORA training set only=true2024.03127.6130.685.383.3122.880.236.245.446.1119.978.337.94343.9————
OSXFine-tuned on AGORA training set or synthetic data=true2023.03127.6130.685.383.3122.880.236.245.446.1119.978.337.94343.9————
PyMaF-Xfinetuned on AGORA training set=true2024.03140141.294.493.5125.7843544.645.6124.683.237.942.543.7————
PyMAF-XFine-tuned on AGORA training set or synthetic data=true2023.03140141.294.493.5125.7843544.645.6124.683.237.942.543.7————
BEDLAMfinetuned on AGORA training set=true2024.03141142.2102.1101.8103.874.523.131.733.2102.974.324.729.931.3————
Hand4Wholefinetuned on AGORA training set=true2024.03141.1144.19692.7135.590.241.646.348.1132.687.146.144.346.2————
Hand4WholeFine-tuned on AGORA training set or synthetic data=true2023.03141.1144.19692.7135.590.241.646.348.1132.687.146.144.346.2————
PAREProjection type=weak perspective, Fine-tuned on AGORA=false2023.03146.2——————————————140.9——
SPINProjection type=weak perspective, Fine-tuned on AGORA=true2023.03153.4——————————————148.9——
PAREMethod categorization=Top-down2024.03174167.7——140.9————146.2————0.84—0.960.75
BEDLAM2024.03177.5179.5132.2131.413196.525.838.839129.695.927.836.636.7————
SPIN2022.11199.2193.4——148.9————153.4————0.77———
PyMAFMethod categorization=Top-down2024.03207.4200.2——168.2————174.2————0.84—0.860.82
HMRMethod categorization=Top-down2024.03226217——173.6————180.5————0.8—0.930.7
PIXIEFine-tuned on AGORA training set or synthetic data=false2023.03230.9233.9173.4171.1191.8142.250.249.549189.3140.354.546.446————
ExPoseFine-tuned on AGORA training set or synthetic data=false2023.03263.3265184.8183.4217.3151.551.174.971.3215.9150.455.272.568.8————
SMPLify-XFine-tuned on AGORA training set or synthetic data=false2023.03326.5333.1263.3256.5236.518748.948.351.4231.8182.152.946.549.6————
BEVBody Model=SMPL, fine-tuned on AGORA=true2022.07—————100.7————105.3———————
ExPoseBody Model=SMPL-X, fine-tuned on AGORA=false2022.07————217.3151.551.174.971.3215.9150.455.272.568.8————
FrankMocapFine-tuned on AGORA training set or synthetic data=false2023.03——207.8204—168.3—54.755.7—165.2—52.353.1————
FrankMocapBody Model=SMPL-X, fine-tuned on AGORA=false2022.07—————168.3—54.755.7—165.2—52.353.1————
Hand4WholeBody Model=SMPL-X, fine-tuned on AGORA=true2022.07————135.590.241.646.348.1132.687.146.144.346.2————
PAREBody Model=SMPL, fine-tuned on AGORA=true2022.07—————140.9————146.2———————
PIXIEBody Model=SMPL-X, fine-tuned on AGORA=false2022.07————191.8142.250.249.549189.3140.354.546.446————
PyMAF-X (HR48)Body Model=SMPL-X, fine-tuned on AGORA=true, backbone=HRNet-482022.07————125.7843544.645.6124.683.237.942.543.7————
PyMAF-X (Res50)Body Model=SMPL-X, fine-tuned on AGORA=true, backbone=ResNet-502022.07————134.490.438.745.947.3132.88942.243.945.4————
ROMPBody Model=SMPL, fine-tuned on AGORA=true2022.07—————103.4————108.1———————
SMPLify-XBody Model=SMPL-X, fine-tuned on AGORA=false2022.07————236.518748.948.351.4231.8182.152.946.549.6————
SPECBody Model=SMPL, fine-tuned on AGORA=true2022.07—————106.5————112.3———————
SPINBody Model=SMPL, fine-tuned on AGORA=true2022.07—————148.9————153.4———————