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 201–210 of 271 papers

TitleStatusHype
Plateau-reduced Differentiable Path Tracing—0
Learning to Rasterize DifferentiablyCode0
Learning-based Inverse Rendering of Complex Indoor Scenes with Differentiable Monte Carlo Raytracing—0
Random Weight Factorization Improves the Training of Continuous Neural Representations—0
A General Scattering Phase Function for Inverse Rendering—0
PRIF: Primary Ray-based Implicit Function—0
Deep Uncalibrated Photometric Stereo via Inter-Intra Image Feature Fusion—0
PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo—0
DeepPS2: Revisiting Photometric Stereo Using Two Differently Illuminated ImagesCode0
GAN2X: Non-Lambertian Inverse Rendering of Image GANs—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