In this supplemental document, we demonstrate more results of the scenes in the main paper: "Gradient-Domain Volumetric Photon Density Estimation". The primal- and gradient-domain techniques included are:
The source code (Mistuba implementation) with instruction can be found at the following address: Github repo
Scenes (Mitsuba format) and the reference: You can download each scene individually by clicking on the scene's name below. Please note that some scenes have a Copyright. Refer to the acknowledgment section inside the paper.
Equal-time comparisons are shown for the below scenes. We first show interactive 4-way comparisons between our method and other methods. Each visual comparison includes:
| Scene | Equal-time comparison | Reference | Comments |
|---|---|---|---|
| Kitchen |
5 min 30 min |
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A complex scene with diffuse and specular light transport in homogeneous media with anisotropic phase function (g = 0.3). |
| Staircase |
2 min 30 min |
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A scene with only diffuse light transport and isotropic phase function. |
| Bathroom |
5 min 30 min |
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A complex scene with diffuse and specular light transport in homogeneous media with anisotropic phase function. |
| Spotlight |
10 min 30 min |
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An even more challenging scene with dominant specular light transport and anisotropic phase function (g = 0.3). |
| g = 0.0 | g = 0.225 | g = 0.45 | g = 0.675 | g = 0.9 |
|---|---|---|---|---|
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| 10 min | 10 min | 10 min | 10 min | 10 min |
| Scene | Equal-time comparison | Reference | Comments |
|---|---|---|---|
| Glass |
5 min |
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A complex scene with a glass of milk and a glass of orange juice. Manifold exploration is used to handle the dielectric interfaces. |
| Scene | Equal-time comparison | Reference | Comments |
|---|---|---|---|
| Kitchen |
5 min (VPM) 5 min (BRE) 5 min (Beam) |
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This presents the experiments with various kernel sizes in our technique. In general, our technique is not quite sensitive with kernel radius size unless it is set too large which causes too strong bias. Gradient-domain techniques take more time per iteration for estimate gradients to reduce variance, and so it is generally slower in reducing bias in progressive rendering. |