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Research map / 3D vision / Human pose estimation

Model-Based 3D Hand Reconstruction via Self-Supervised Learning

CVPR 2021 · 3D vision › Human pose estimation · approach: Depth-based hand pose regression · 122 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add bone-orientation loss E_ori (ablation)S²HAND 3D branch · FreiHAND testMPJPE: 1.54 -> 1.24Helped
Add bone-orientation loss E_ori (ablation)S²HAND 3D branch · FreiHAND testMPVPE: 1.58 -> 1.26Helped
Add a trainable 2D keypoint branch and 2D-3D consistency loss (ablation)S²HAND · FreiHAND testMPJPE: 1.24 -> 1.19Helped
Add a trainable 2D keypoint branch and 2D-3D consistency loss (ablation)S²HAND · FreiHAND testMPVPE: 1.26 -> 1.20Helped
Add photometric consistency loss E_photo (ablation)S²HAND · FreiHAND testMPJPE: 1.19 -> 1.18Helped
Add photometric consistency loss E_photo (ablation)S²HAND · FreiHAND testMPVPE: 1.20 -> 1.19Helped
Use self-supervision with detected 2D keypoints instead of ground-truth 2D keypoints (ablation)S²HAND · FreiHANDAUC_J: 0.730 -> 0.766Helped
Use self-supervision with detected 2D keypoints instead of ground-truth 2D keypoints (ablation)S²HAND · HO-3DAUC_J: 0.765 -> 0.773Helped
Finetune the 2D and 3D branches with 2D-3D consistency (ablation)S²HAND 2D branch · FreiHAND training set2D AUC, Per Joint: 0.820 -> 0.828Helped
Finetune the 2D and 3D branches with 2D-3D consistency (ablation)S²HAND 3D branch · FreiHAND training set2D AUC, Per Joint: 0.808 -> 0.825Helped
Use texture modeling (ablation)S²HAND · FreiHAND test3D shape reconstructionNo clear effect
Use S²HAND instead of MANO-CNN under self-supervisionFreiHAND test, unaligned output · FreiHAND testMPJPE: 12.75 -> 10.57Helped

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