Research map / 3D vision / Depth and stereo
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Monte Carlo shading instead of spherical harmonics lighting | DIB-R++ · Metallic-Surfaces | Light: 0.220 -> 0.074 | Helped |
| Use Monte Carlo shading instead of spherical harmonics lighting | DIB-R++ · Metallic-Surfaces | Tex.: 0.206 -> 0.152 | Helped |
| Use spherical Gaussian shading instead of spherical harmonics lighting | DIB-R++ · Metallic-Surfaces | Light: 0.220 -> 0.095 | Helped |
| Use spherical Gaussian shading instead of spherical harmonics lighting | DIB-R++ · Metallic-Surfaces | Tex.: 0.206 -> 0.218 | No clear effect |
| Use Monte Carlo shading instead of spherical harmonics lighting | DIB-R++ · Glossy-Surfaces | Light: 0.131 -> 0.106 | Helped |
| Use spherical Gaussian shading instead of spherical harmonics lighting | DIB-R++ · Glossy-Surfaces | Light: 0.131 -> 0.091 | Helped |
| Use spherical Gaussian shading instead of Monte Carlo shading | DIB-R++ · Glossy-Surfaces | Light: 0.106 -> 0.091 | Helped |
| Use spherical Gaussian shading instead of Monte Carlo shading | DIB-R++ · Glossy-Surfaces | Tex.: 0.142 -> 0.140 | Helped |
| Use Monte Carlo shading instead of spherical Gaussian shading | DIB-R++ · Metallic-Surfaces | Light: 0.095 -> 0.074 | Helped |
| Use Monte Carlo shading instead of spherical Gaussian shading | DIB-R++ · Metallic-Surfaces | Tex.: 0.218 -> 0.152 | Helped |
| Use Monte Carlo shading instead of spherical Gaussian shading | DIB-R++ · Glossy-Surfaces | Light: 0.091 -> 0.106 | Hurt |
Closest papers by meaning
- Eclipse: Disambiguating Illumination and Materials using Unintended Shadows (CVPR 2024 · similarity 0.90)
- Material Palette: Extraction of Materials from a Single Image (CVPR 2024 · similarity 0.89)
- Inverse Rendering of Glossy Objects via the Neural Plenoptic Function and Radiance Fields (CVPR 2024 · similarity 0.89)
- Diffusion Renderer: Neural Inverse and Forward Rendering with Video Diffusion Models (CVPR 2025 · similarity 0.89)
- PBR-NeRF: Inverse Rendering with Physics-Based Neural Fields (CVPR 2025 · similarity 0.89)
- Inverse Rendering using Multi-Bounce Path Tracing and Reservoir Sampling (ICLR 2025 · similarity 0.88)
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