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 121–130 of 271 papers

TitleStatusHype
Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting—0
IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination—0
Inferring Fluid Dynamics via Inverse Rendering—0
DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models—0
LightLab: Controlling Light Sources in Images with Diffusion Models—0
Diffusion Renderer: Neural Inverse and Forward Rendering with Video Diffusion Models—0
Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images—0
A Bayesian Inference Framework for Procedural Material Parameter Estimation—0
IllumiNeRF: 3D Relighting Without Inverse Rendering—0
Identity-Expression Ambiguity in 3D Morphable Face Models—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