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
Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering—0
Phys3DGS: Physically-based 3D Gaussian Splatting for Inverse Rendering—0
PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations—0
PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting—0
Physically-Based Editing of Indoor Scene Lighting from a Single Image—0
Plateau-reduced Differentiable Path Tracing—0
Pointersect: Neural Rendering with Cloud-Ray Intersection—0
Polarimetric Multi-View Inverse Rendering—0
Polarimetric Multi-View Inverse Rendering—0
Practical and Accurate Reconstruction of an Illuminant's Spectral Power Distribution for Inverse Rendering Pipelines—0
PRIF: Primary Ray-based Implicit Function—0
Progressive Radiance Distillation for Inverse Rendering with Gaussian Splatting—0
PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo—0
Q-NET: A Network for Low-Dimensional Integrals of Neural Proxies—0
Radar Fields: An Extension of Radiance Fields to SAR—0
Random Weight Factorization Improves the Training of Continuous Neural Representations—0
Refining 6D Object Pose Predictions using Abstract Render-and-Compare—0
Relightable and Animatable Neural Avatar from Sparse-View Video—0
Relighting Humans: Occlusion-Aware Inverse Rendering for Full-Body Human Images—0
RelitLRM: Generative Relightable Radiance for Large Reconstruction Models—0
ReNeRF: Relightable Neural Radiance Fields with Nearfield Lighting—0
RGBX: Image decomposition and synthesis using material- and lighting-aware diffusion models—0
RGS-DR: Reflective Gaussian Surfels with Deferred Rendering for Shiny Objects—0
RISE-SDF: a Relightable Information-Shared Signed Distance Field for Glossy Object 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