This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization

Last update: Dec 14, 2022

Overview

Spherical Gaussian Optimization

This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization. This code has been used in the following paper to generate ground-truth spherical Gaussian parameters.

Li, Z., Shafiei, M., Ramamoorthi, R., Sunkavalli, K., & Chandraker, M. (2020). Inverse rendering for complex indoor scenes: Shape, spatially-varying lighting and svbrdf from a single image. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2475-2484).

Please cite the paper if you find the code to be useful in your own project. Please refer to the papers for more implementation details.

Instructions

To run the code, use the command python optimEnvSplit.py --cuda --dataRoot DATA, where DATA is the path to the synthetic dataset.

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Comments

About format of spatially-varying lighting!
Hi, @lzqsd

I'd like to ask about the format of spatially-varying lighting.

In this Figure (f), you show the spatially-varying lighting. However, I've never seen this representation such as a grid cell.

I have three questions.

Can this HDR render the lighting without converting a format in Blender?

How did you create this ground truth HDR?

Additionally, If you know references about this format, please let me introduce it.

Best regards,
opened by UdonDa 0
How to make the parameters visualized?

Hi, This code may generate the spherical guassian parameters. How to get the image of spherical guassian parameters? Just like you had presented the image results of 12 SG lobes.

opened by Mrwjm 1

Owner

GitHub

DiffQ performs differentiable quantization using pseudo quantization noise. It can automatically tune the number of bits used per weight or group of weights, in order to achieve a given trade-off between model size and accuracy.

Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto

145 Dec 30, 2022

This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization

Related tags

Overview

Spherical Gaussian Optimization

Instructions

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