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 1–25 of 271 papers

TitleStatusHype
Colorful Diffuse Intrinsic Image Decomposition in the WildCode3
Segment Anything in 3D with Radiance FieldsCode3
Inferring Articulated Rigid Body Dynamics from RGBD VideoCode3
Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object RelightingCode2
GS-IR: 3D Gaussian Splatting for Inverse RenderingCode2
Intrinsic Image Decomposition via Ordinal ShadingCode2
TensoIR: Tensorial Inverse RenderingCode2
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and DenoisingCode2
Extracting Triangular 3D Models, Materials, and Lighting From ImagesCode2
ADOP: Approximate Differentiable One-Pixel Point RenderingCode2
Modular Primitives for High-Performance Differentiable RenderingCode2
SVG-IR: Spatially-Varying Gaussian Splatting for Inverse RenderingCode1
TensoFlow: Tensorial Flow-based Sampler for Inverse RenderingCode1
Materialist: Physically Based Editing Using Single-Image Inverse RenderingCode1
PBR-NeRF: Inverse Rendering with Physics-Based Neural FieldsCode1
Triplet: Triangle Patchlet for Mesh-Based Inverse Rendering and Scene Parameters ApproximationCode1
A General Albedo Recovery Approach for Aerial Photogrammetric Images through Inverse RenderingCode1
MAIR++: Improving Multi-view Attention Inverse Rendering with Implicit Lighting RepresentationCode1
PIR: Photometric Inverse Rendering with Shading Cues Modeling and Surface Reflectance RegularizationCode1
Dynamic Scene Understanding through Object-Centric Voxelization and Neural RenderingCode1
Uncertainty for SVBRDF Acquisition using Frequency AnalysisCode1
Spin-UP: Spin Light for Natural Light Uncalibrated Photometric StereoCode1
High-Quality Mesh Blendshape Generation from Face Videos via Neural Inverse RenderingCode1
GIR: 3D Gaussian Inverse Rendering for Relightable Scene FactorizationCode1
IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray TracingCode1
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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