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 51–100 of 271 papers

TitleStatusHype
A Morphable Face Albedo ModelCode1
The Sky's the Limit: Re-lightable Outdoor Scenes via a Sky-pixel Constrained Illumination Prior and Outside-In VisibilityCode1
Dynamic Scene Understanding through Object-Centric Voxelization and Neural RenderingCode1
Triplet: Triangle Patchlet for Mesh-Based Inverse Rendering and Scene Parameters ApproximationCode1
Polarimetric Inverse Rendering for Transparent Shapes ReconstructionCode1
Advances in Neural RenderingCode1
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collectionsCode1
IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray TracingCode1
Multiview Textured Mesh Recovery by Differentiable RenderingCode1
Inverse Rendering of Translucent Objects using Physical and Neural RenderersCode1
IBL-NeRF: Image-Based Lighting Formulation of Neural Radiance FieldsCode1
IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View SynthesisCode1
InverseRenderNet: Learning single image inverse renderingCode1
Outdoor inverse rendering from a single image using multiview self-supervisionCode1
MAIR: Multi-view Attention Inverse Rendering with 3D Spatially-Varying Lighting EstimationCode1
Spelunking the Deep: Guaranteed Queries on General Neural Implicit Surfaces via Range AnalysisCode1
Invertible Neural BRDF for Object Inverse RenderingCode1
DeepPS2: Revisiting Photometric Stereo Using Two Differently Illuminated ImagesCode0
All-frequency Full-body Human Image RelightingCode0
TextureSplat: Per-Primitive Texture Mapping for Reflective Gaussian SplattingCode0
UniVoxel: Fast Inverse Rendering by Unified Voxelization of Scene RepresentationCode0
Virtual Home Staging: Inverse Rendering and Editing an Indoor Panorama under Natural IlluminationCode0
Shadow Art Kanji: Inverse Rendering ApplicationCode0
SfSNet: Learning Shape, Reflectance and Illuminance of Faces in the WildCode0
Differentiable Surface Splatting for Point-based Geometry ProcessingCode0
RenderNet: A deep convolutional network for differentiable rendering from 3D shapesCode0
Physically Disentangled RepresentationsCode0
NOVUM: Neural Object Volumes for Robust Object ClassificationCode0
ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail TransferCode0
Differentiable Monte Carlo Ray Tracing through Edge SamplingCode0
Light Sampling Field and BRDF Representation for Physically-based Neural RenderingCode0
Fine-Grained Multi-View Hand Reconstruction Using Inverse RenderingCode0
IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor ScenesCode0
Face Inverse Rendering via Hierarchical DecouplingCode0
Deep Single-Image Portrait RelightingCode0
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single ImageCode0
Learning to Rasterize DifferentiablyCode0
Neural Lumigraph RenderingCode0
Epi-NAF: Enhancing Neural Attenuation Fields for Limited-Angle CT with Epipolar Consistency Conditions—0
Environment Maps Editing using Inverse Rendering and Adversarial Implicit Functions—0
End-to-end 3D shape inverse rendering of different classes of objects from a single input image—0
Deep Polarization Cues for Single-shot Shape and Subsurface Scattering Estimation—0
A Theory of Topological Derivatives for Inverse Rendering of Geometry—0
Efficient Perspective-Correct 3D Gaussian Splatting Using Hybrid Transparency—0
Efficient multi-view training for 3D Gaussian Splatting—0
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering—0
Efficient Multi-View Inverse Rendering Using a Hybrid Differentiable Rendering Method—0
Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering—0
A Simple Approach to Differentiable Rendering of SDFs—0
Eclipse: Disambiguating Illumination and Materials using Unintended Shadows—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