SOTAVerified

Inverse Rendering

Inverse Rendering is the task of recovering the properties of a scene, such as shape, material, and lighting, from an image or a video. The goal of inverse rendering is to determine the properties of a scene given an observation of it, and to generate new images or videos based on these properties.

Papers

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Showing 151–160 of 271 papers

TitleStatusHype
Robust Category-Level 3D Pose Estimation from Synthetic Data—0
Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior—0
Scattering Parameters and Surface Normals from Homogeneous Translucent Materials using Photometric Stereo—0
ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering—0
SfSNet: Learning Shape, Reflectance and Illuminance of Faces `in the Wild'—0
Shading Annotations in the Wild—0
Shading Meets Motion: Self-supervised Indoor 3D Reconstruction Via Simultaneous Shape-from-Shading and Structure-from-Motion—0
SHINOBI: Shape and Illumination using Neural Object Decomposition via BRDF Optimization In-the-wild—0
Simultaneous Estimation of Near IR BRDF and Fine-Scale Surface Geometry—0
Single-Image 3D Human Digitization with Shape-Guided Diffusion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural-PBIRHDR-PSNR26.01—Unverified
2NVDiffRecMCHDR-PSNR24.43—Unverified
3InvRenderHDR-PSNR23.76—Unverified
4NeRFactorHDR-PSNR23.54—Unverified
5NeRDHDR-PSNR23.29—Unverified
6NVDiffRecHDR-PSNR22.91—Unverified
7PhySGHDR-PSNR21.81—Unverified