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

Showing 4150 of 271 papers

TitleStatusHype
NDJIR: Neural Direct and Joint Inverse Rendering for Geometry, Lights, and Materials of Real ObjectCode1
Multi-view Inverse Rendering for Large-scale Real-world Indoor ScenesCode1
IBL-NeRF: Image-Based Lighting Formulation of Neural Radiance FieldsCode1
IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View SynthesisCode1
Polarimetric Inverse Rendering for Transparent Shapes ReconstructionCode1
Sobolev Training for Implicit Neural Representations with Approximated Image DerivativesCode1
Self-calibrating Photometric Stereo by Neural Inverse RenderingCode1
Sparse Ellipsometry: Portable Acquisition of Polarimetric SVBRDF and Shape with Unstructured Flash PhotographyCode1
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collectionsCode1
Multiview Textured Mesh Recovery by Differentiable RenderingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural-PBIRHDR-PSNR26.01Unverified
2NVDiffRecMCHDR-PSNR24.43Unverified
3InvRenderHDR-PSNR23.76Unverified
4NeRFactorHDR-PSNR23.54Unverified
5NeRDHDR-PSNR23.29Unverified
6NVDiffRecHDR-PSNR22.91Unverified
7PhySGHDR-PSNR21.81Unverified