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Research map / 3D vision / Face and shape

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

NeurIPS 2020 · 3D vision › Face and shape · approach: Neural implicit surface reconstruction · 145 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use IDR instead of Colmap trim=0DTU fixed-camera watertight reconstruction · DTUChamfer-L1 (mm): 1.36 -> 0.9Helped
Use IDR instead of Colmap trim=0DTU fixed-camera reconstruction · DTUPSNR: 20.58 -> 23.20Helped
Use IDR instead of Colmap trim=7DTU fixed-camera trimmed reconstruction · DTUChamfer-L1 (mm): 0.65 -> 0.9Hurt
Use IDR instead of Colmap trim=7DTU fixed-camera trimmed reconstruction · DTUPSNR: 18.54 -> 23.20Helped
Optimize camera parameters jointly with geometry instead of fixing inaccurate initial cameras (ablation)IDR · DTU scan 114reconstruction qualityHelped
Add viewing direction to the renderer (ablation)IDR · DTU scan 114reconstruction qualityHelped
Add surface normal to the renderer (ablation)IDR · DTU scan 114 and geometry-appearance transfergeometry-appearance separationHelped
Add global geometry feature vector to the renderer (ablation)IDR · DTU scan 114reconstruction qualityHelped
Jointly estimate cameras and reconstruct geometry instead of using ColmapIDR · Fountain-P11R_error (deg): 0.03 -> 0.02Helped
Jointly estimate cameras and reconstruct geometry instead of using ColmapIDR · Fountain-P11t_error (mm): 2.86 -> 2.02Helped
Use IDR instead of ColmapFountain-P11 · Fountain-P11PSNR: 21.99 -> 26.48Helped
Evaluate on held-out images rather than training imagesIDR · DTU fixed ground-truth camerasPSNR: 23.34 -> 22.55Hurt

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