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 151–175 of 271 papers

TitleStatusHype
Robust Category-Level 3D Pose Estimation from Synthetic Data—0
Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior—0
Scattering Parameters and Surface Normals from Homogeneous Translucent Materials using Photometric Stereo—0
ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering—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
Deep Face Feature for Face Alignment—0
Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering—0
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering—0
Deep Polarization Cues for Single-shot Shape and Subsurface Scattering Estimation—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