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PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting

About

We present PhySG, an end-to-end inverse rendering pipeline that includes a fully differentiable renderer and can reconstruct geometry, materials, and illumination from scratch from a set of RGB input images. Our framework represents specular BRDFs and environmental illumination using mixtures of spherical Gaussians, and represents geometry as a signed distance function parameterized as a Multi-Layer Perceptron. The use of spherical Gaussians allows us to efficiently solve for approximate light transport, and our method works on scenes with challenging non-Lambertian reflectance captured under natural, static illumination. We demonstrate, with both synthetic and real data, that our reconstructions not only enable rendering of novel viewpoints, but also physics-based appearance editing of materials and illumination.

Kai Zhang, Fujun Luan, Qianqian Wang, Kavita Bala, Noah Snavely• 2021

Related benchmarks

TaskDatasetResultRank
Novel View SynthesisBlender (test)
PSNR20.6
37
Novel Scene RelightingStanford-ORB 1.0 (test)
PSNR-H21.81
26
Novel View SynthesisNeRF Synthetic Blender (test)
Avg PSNR18.91
24
Novel View SynthesisStanford-ORB 1.0 (test)
PSNR-H24.24
18
RelightingSynthetic Scenes (test)
PSNR22.6288
16
Novel View SynthesisDTU 15 (test)
PSNR19.11
15
Novel View SynthesisSynthetic Dataset (test)
PSNR31.0425
13
Novel View SynthesisShiny Blender
PSNR26.21
13
Geometry EstimationStanfordORB
Depth Error1.9
11
Albedo EstimationSynthetic Dataset (test)
PSNR19.7933
10
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