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

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Showing 201–210 of 271 papers

TitleStatusHype
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
DeepShaRM: Multi-View Shape and Reflectance Map Recovery Under Unknown Lighting—0
Deep Structure for end-to-end inverse rendering—0
Deep Uncalibrated Photometric Stereo via Inter-Intra Image Feature Fusion—0
DEL: Discrete Element Learner for Learning 3D Particle Dynamics with Neural Rendering—0
DiffCSG: Differentiable CSG via Rasterization—0
Differentiable Inverse Rendering with Interpretable Basis BRDFs—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