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Research map / 3D vision / Face and shape

Multi-View Reconstruction Using Signed Ray Distance Functions (SRDF)

CVPR 2023 · 3D vision › Face and shape · approach: Neural implicit surface reconstruction · 10 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use SRDF-based volumetric depth optimization instead of differentiable renderingMulti-view 3D reconstruction · DTUChamfer Distance: 0.69 -> 0.36Helped
Use SRDF-based volumetric depth optimization instead of classic MVSMulti-view 3D reconstruction · DTUChamfer Distance: 0.42 -> 0.36Helped
Use SRDF-based volumetric depth optimization instead of deep MVSMulti-view 3D reconstruction · DTUChamfer Distance: 0.38 -> 0.36Helped
Use SRDF-based volumetric depth optimization instead of CasMVSNetMulti-view 3D reconstruction · DTUAccuracy: 0.34 -> 0.37Hurt
Use SRDF-based volumetric depth optimization instead of PatchmatchNetMulti-view 3D reconstruction · DTUCompleteness: 0.35 -> 0.36Hurt
Use the learned photo-consistency prior instead of the median-color baseline priorSRDF reconstruction · Real imagesreconstruction qualityHelped
Use the median-color baseline photo-consistency priorSRDF reconstruction · Renderpeople synthetic datareconstruction qualityHelped
Optimize PatchmatchNet depth results with SRDFPatchmatchNet reconstruction · Multi-view human reconstructionsurface detail and noiseHelped
Optimize PatchmatchNet depth results with SRDFPatchmatchNet reconstruction · Multi-view human reconstructionrecovery from large geometric errorsHurt

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