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Research map / 3D vision / Face and shape

AUV-Net: Learning Aligned UV Maps for Texture Transfer and Synthesis

CVPR 2022 · 3D vision › Face and shape · approach: Textured mesh generation · 29 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add color loss L_c (ablation)AUV-Net · ShapeNet carsIOU: 68.5 -> 72.7Helped
Add color loss L_c (ablation)AUV-Net · ShapeNet chairsIOU: 85.2 -> 85.8No clear effect
Add normal loss L_n (ablation)AUV-Net · ShapeNet cars and chairsIOU: Cars: 71.7 -> 72.7; chairs: 84.6 -> 85.8Helped
Add cycle loss L_x (ablation)AUV-Net · ShapeNet cars and chairsIOU: Cars: 73.0 -> 72.7; chairs: 83.7 -> 85.8Mixed
Add smoothness loss L_s (ablation)AUV-Net · ShapeNet cars and chairsIOU: Cars: 72.8 -> 72.7; chairs: 87.1 -> 85.8Mixed
Add prior loss L_p (ablation)AUV-Net · ShapeNet cars and chairsIOU: Cars: 70.6 -> 72.7; chairs: 85.7 -> 85.8Helped
Add masker (ablation)AUV-Net · ShapeNet cars and chairsIOU: Cars: 72.0 -> 72.7; chairs: 71.1 -> 85.8Helped
Use aligned texture maps for texture generation instead of Texture FieldsTexture synthesis · Triplegangers headsFID: 24.59 -> 5.69Helped
Use aligned texture maps for texture generation instead of Texture FieldsTexture synthesis · ShapeNet cars and chairsFID: Cars: 53.09 -> 12.11; chairs: 7.03 -> 5.33Helped
Use AUV-Net rather than Texture Fields for textured single-view reconstructionTextured single-view reconstruction · ShapeNet cars and chairsFID: Cars: 92.89 -> 40.85; chairs: 36.89 -> 33.26Helped
Use AUV-Net rather than Texture Fields for textured single-view reconstructionTextured single-view reconstruction · ShapeNet cars and chairsSSIM: Cars: 0.897 -> 0.894; chairs: 0.855 -> 0.853Hurt
Use AUV-Net rather than Texture Fields for textured single-view reconstructionTextured single-view reconstruction · ShapeNet cars and chairsfeature-l1: Cars: 0.219 -> 0.186; chairs: 0.193 -> 0.189Helped

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