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 231–240 of 271 papers

TitleStatusHype
Joint Learning of Portrait Intrinsic Decomposition and Relighting—0
NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning—0
OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets—0
Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images—0
Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance—0
PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting—0
Neural Lumigraph RenderingCode0
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering—0
Uncalibrated Neural Inverse Rendering for Photometric Stereo of General Surfaces—0
MaterialGAN: Reflectance Capture using a Generative SVBRDF Model—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