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 126–150 of 271 papers

TitleStatusHype
PBIR-NIE: Glossy Object Capture under Non-Distant Lighting—0
Many-Worlds Inverse Rendering—0
UniVoxel: Fast Inverse Rendering by Unified Voxelization of Scene RepresentationCode0
Surfel-based Gaussian Inverse Rendering for Fast and Relightable Dynamic Human Reconstruction from Monocular Video—0
SS-SfP:Neural Inverse Rendering for Self Supervised Shape from (Mixed) Polarization—0
Deep Polarization Cues for Single-shot Shape and Subsurface Scattering Estimation—0
Multi-times Monte Carlo Rendering for Inter-reflection Reconstruction—0
Fine-Grained Multi-View Hand Reconstruction Using Inverse RenderingCode0
Blind Inversion using Latent Diffusion Priors—0
Intrinsic PAPR for Point-level 3D Scene Albedo and Shading Editing—0
Inverse Rendering using Multi-Bounce Path Tracing and Reservoir Sampling—0
IllumiNeRF: 3D Relighting Without Inverse Rendering—0
3D Reconstruction with Fast Dipole Sums—0
Don't Splat your Gaussians: Volumetric Ray-Traced Primitives for Modeling and Rendering Scattering and Emissive Media—0
GS-ROR^2: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction—0
A Simple Approach to Differentiable Rendering of SDFs—0
RGBX: Image decomposition and synthesis using material- and lighting-aware diffusion models—0
ESR-NeRF: Emissive Source Reconstruction Using LDR Multi-view Images—0
Unveiling the Ambiguity in Neural Inverse Rendering: A Parameter Compensation Analysis—0
Inverse Neural Rendering for Explainable Multi-Object Tracking—0
IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination—0
PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations—0
Dr.Hair: Reconstructing Scalp-Connected Hair Strands without Pre-training via Differentiable Rendering of Line Segments—0
Inverse Rendering of Glossy Objects via the Neural Plenoptic Function and Radiance Fields—0
GaNI: Global and Near Field Illumination Aware Neural Inverse Rendering—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