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LISA: Learning Implicit Shape and Appearance of Hands

CVPR 2022 · 3D vision › Face and shape · approach: Pixel-aligned implicit human and hand reconstruction · 69 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use per-bone SDF and color predictions blended by learned skinning weightsLISA · 3DH and MANO point-cloud testsV2V [mm]: 3.05 -> 2.93; 3.14 -> 3.09Helped
Add the geometric prior to image training (ablation)LISA-im · 3DH and MANO point-cloud tests, reconstruction to scanV2V [mm]: 2.93 -> 1.93; 3.09 -> 1.45Helped
Train only with the geometric prior instead of images (ablation)LISA · 3DH and MANO point-cloud tests, reconstruction to scanV2V [mm]: 2.93 -> 0.83; 3.09 -> 0.36Helped
Add the geometric prior to image training (ablation)LISA-im · DeepHandMesh, 1 viewV2V: 5.48 -> 3.84Helped
Add the geometric prior to image training (ablation)LISA-im · DeepHandMesh, 2 and 4 viewsV2V: 3.86 -> 3.70; 3.62 -> 3.53Helped
Add the geometric prior to image training (ablation)LISA-im · DeepHandMesh, 1 viewPSNR: 25.04 -> 25.43Helped
Add the geometric prior to image training (ablation)LISA-im · InterHand2.6M color reconstruction, 1 viewLPIPS: 0.08 -> 0.06Helped
Add the geometric prior to image training (ablation)LISA-im · InterHand2.6M color reconstruction, 2 viewsLPIPS: 0.07 -> 0.06Helped
Add the geometric prior to image training (ablation)LISA-im · InterHand2.6M color reconstruction, 4 viewsLPIPS: 0.07 -> 0.05Helped
Use images and geometric prior together rather than the geometric prior alone (ablation)LISA-geom · 3DH point-cloud test, reconstruction to scanV2V [mm]: 0.83 -> 1.93Hurt
Use images and geometric prior together rather than the geometric prior alone (ablation)LISA-geom · MANO point-cloud test, reconstruction to scanV2V [mm]: 0.36 -> 1.45Hurt
Use the geometric prior in image reconstruction (ablation)LISA-im · DeepHandMesh novel-view color reconstructionPSNR: 1 view: 25.04 -> 25.43; 2 views: 29.84 -> 29.40; 4 views: 30.21 -> 29.69Mixed

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