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 181–190 of 271 papers

TitleStatusHype
ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering—0
Neural-PBIR Reconstruction of Shape, Material, and Illumination—0
Pointersect: Neural Rendering with Cloud-Ray Intersection—0
Light Sampling Field and BRDF Representation for Physically-based Neural RenderingCode0
Inferring Fluid Dynamics via Inverse Rendering—0
Neural Fields meet Explicit Geometric Representation for Inverse Rendering of Urban Scenes—0
Neural Microfacet Fields for Inverse Rendering—0
Weakly-supervised Single-view Image Relighting—0
MELON: NeRF with Unposed Images in SO(3)—0
Hardware Acceleration of Neural Graphics—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