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Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition

NeurIPS 2021 · 3D vision › NeRF and radiance fields · approach: Few-shot neural rendering architectures · 19 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use Neural-PIL instead of MC integrationIllumination estimation · 6 rendered spheres, roughness 0.2 and 0.5PSNR: 34.88 -> 35.76; 35.14 -> 35.28Helped
Use Neural-PIL instead of spherical GaussiansIllumination estimation · 6 rendered spheres, roughness 0.2 and 0.5PSNR: 31.57 -> 35.76; 28.98 -> 35.28Helped
Use the proposed decomposition method rather than NeRDBRDF decomposition · Globe, Car, ChairDiffuse PSNR: 18.24 -> 20.22Helped
Use the proposed decomposition method rather than NeRDBRDF decomposition · Globe, Car, ChairSpecular PSNR: 25.70 -> 16.84Hurt
Use the proposed decomposition method rather than NeRDBRDF decomposition · Globe, Car, ChairRoughness PSNR: 15.00 -> 24.82Helped
Use the proposed method rather than NeRFView synthesis · SyntheticPSNR: 34.24 -> 30.08Hurt
Use the proposed method rather than NeRDView synthesis and relighting · SyntheticPSNR: 27.96 -> 29.24Helped
Use the proposed method rather than NeRDView synthesis and relighting · Real-worldPSNR: 25.81 -> 26.23Helped
Add BRDF-SMAE to constrain the BRDF parameter space (ablation)Neural-PIL decomposition method · 3 synthetic scenes under varying illuminationDiffuse PSNR: 11.87 -> 20.22Helped
Add BRDF-SMAE to constrain the BRDF parameter space (ablation)Neural-PIL decomposition method · 3 synthetic scenes under varying illuminationSpecular PSNR: 9.24 -> 16.84Helped
Add BRDF-SMAE to constrain the BRDF parameter space (ablation)Neural-PIL decomposition method · 3 synthetic scenes under varying illuminationRoughness PSNR: 16.51 -> 24.82Helped

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