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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 271 papers

TitleStatusHype
PANDORA: Polarization-Aided Neural Decomposition Of Radiance—0
Inferring Articulated Rigid Body Dynamics from RGBD VideoCode3
Spatio-Temporal Outdoor Lighting Aggregation on Image Sequences using Transformer Networks—0
Spelunking the Deep: Guaranteed Queries on General Neural Implicit Surfaces via Range AnalysisCode1
NeAT: Neural Adaptive TomographyCode1
CLA-NeRF: Category-Level Articulated Neural Radiance Field—0
Differentiable Neural Radiosity—0
PhyIR: Physics-Based Inverse Rendering for Panoramic Indoor ImagesCode1
Extracting Triangular 3D Models, Materials, and Lighting From ImagesCode2
Advances in Neural RenderingCode1
Survey of Deep Learning Methods for Inverse Problems—0
ADOP: Approximate Differentiable One-Pixel Point RenderingCode2
Accelerating Inverse Rendering By Using a GPU and Reuse of Light Paths—0
Identity-Expression Ambiguity in 3D Morphable Face Models—0
Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting—0
Spatially and color consistent environment lighting estimation using deep neural networks for mixed reality—0
Differentiable Surface Rendering via Non-Differentiable Sampling—0
Modeling Clothing as a Separate Layer for an Animatable Human Avatar—0
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
NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown IlluminationCode1
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
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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