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 176–200 of 271 papers

TitleStatusHype
Unveiling the Ambiguity in Neural Inverse Rendering: A Parameter Compensation Analysis—0
URAvatar: Universal Relightable Gaussian Codec Avatars—0
UrbanIR: Large-Scale Urban Scene Inverse Rendering from a Single Video—0
Vid2Avatar-Pro: Authentic Avatar from Videos in the Wild via Universal Prior—0
VMINer: Versatile Multi-view Inverse Rendering with Near- and Far-field Light Sources—0
Don't Splat your Gaussians: Volumetric Ray-Traced Primitives for Modeling and Rendering Scattering and Emissive Media—0
Weakly-supervised Single-view Image Relighting—0
3D Gaussian Inverse Rendering with Approximated Global Illumination—0
ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields—0
3D Reconstruction with Fast Dipole Sums—0
A Bayesian Inference Framework for Procedural Material Parameter Estimation—0
Accelerating Inverse Rendering By Using a GPU and Reuse of Light Paths—0
Acquisition of Spatially-Varying Reflectance and Surface Normals via Polarized Reflectance Fields—0
RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering—0
A General Scattering Phase Function for Inverse Rendering—0
A Simple Approach to Differentiable Rendering of SDFs—0
A Theory of Topological Derivatives for Inverse Rendering of Geometry—0
BG-Triangle: Bézier Gaussian Triangle for 3D Vectorization and Rendering—0
BG-Triangle: Bezier Gaussian Triangle for 3D Vectorization and Rendering—0
Blind Gain and Phase Calibration via Sparse Spectral Methods—0
Blind Inversion using Latent Diffusion Priors—0
Channel-wise Noise Scheduled Diffusion for Inverse Rendering in Indoor Scenes—0
CLA-NeRF: Category-Level Articulated Neural Radiance Field—0
CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images—0
Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images—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