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AssemblyHands: Towards Egocentric Activity Understanding via 3D Hand Pose Estimation

CVPR 2023 · 3D vision › Human pose estimation · approach: Depth-based hand pose regression · 66 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add iterative refinement that updates hand crops and volume root from the previous prediction (ablation)MVExoNet annotation pipeline · Assembly101 annotation testMPJPE (mm): 5.42~mm to 4.20~mm (22.5% reduction)Helped
add iterative refinement for two rounds (ablation)MVExoNet annotation pipeline · Desktop ActivitiesMPJPE (mm): 21.20~mm ... 13.38~mm (a 36.9% error reduction)Helped
use multi-view volumetric feature fusion instead of standard 2D keypoint triangulationMVExoNet annotation pipeline · Assembly101 annotation testMPJPE (mm): 7.97 -> 4.20Helped
use exocentric multi-view annotation instead of egocentric-only tracking3D hand pose annotation · Assembly101 annotation testMPJPE (mm): 27.55mm -> 4.20Helped
use 2D + Triangulation (OpenPose)hand pose annotation · Assembly101 annotation testPCK-AUC: 48.1 vs 83.4Hurt
train the egocentric estimator on automatic annotations alone rather than manual annotations (ablation)SVEgoNet · Eval-MMPJPE: 3% relative increase in errorHurt
combine manual and automatic training annotations (ablation)SVEgoNet · egocentric hand pose evaluationMPJPEHelped
replace UmeTrack poses with SVEgoNet posesMS-G3D verb classifier · AssemblyHands-Averb accuracy: 50.3 -> 54.7Helped
add object class labels to pose features (ablation)pose-based verb classifier · AssemblyHands-Averb accuracy: 54.7% -> 56.1%Helped
replace UmeTrack poses with SVEgoNet posesMS-G3D verb classifier · Assembly101, six verb classesper-verb accuracy: pick up +2.1%; put down +6.2%; position +13.1%; screw +1.8%; unscrew +4.1%; remove -1.8%Mixed

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