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 31–40 of 271 papers

TitleStatusHype
BG-Triangle: Bezier Gaussian Triangle for 3D Vectorization and Rendering—0
IRGS: Inter-Reflective Gaussian Splatting with 2D Gaussian Ray Tracing—0
Uni-Renderer: Unifying Rendering and Inverse Rendering Via Dual Stream Diffusion—0
GenLit: Reformulating Single-Image Relighting as Video Generation—0
Acquisition of Spatially-Varying Reflectance and Surface Normals via Polarized Reflectance Fields—0
PBR-NeRF: Inverse Rendering with Physics-Based Neural FieldsCode1
MaterialPicker: Multi-Modal Material Generation with Diffusion Transformers—0
Differentiable Inverse Rendering with Interpretable Basis BRDFs—0
NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectrics—0
RenderBender: A Survey on Adversarial Attacks Using Differentiable 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