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 111–120 of 271 papers

TitleStatusHype
Hardware Acceleration of Neural Graphics—0
CLA-NeRF: Category-Level Articulated Neural Radiance Field—0
Acquisition of Spatially-Varying Reflectance and Surface Normals via Polarized Reflectance Fields—0
IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images—0
IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images—0
Joint Learning of Portrait Intrinsic Decomposition and Relighting—0
Joint Sampling and Optimisation for Inverse Rendering—0
Learning 3D-Gaussian Simulators from RGB Videos—0
GUS-IR: Gaussian Splatting with Unified Shading for Inverse Rendering—0
GS-ROR^2: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction—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