ipme
surface_normal_uncertainty
ipme | surface_normal_uncertainty | |
---|---|---|
1 | 1 | |
24 | 196 | |
- | - | |
0.0 | 10.0 | |
over 1 year ago | over 1 year ago | |
Python | Python | |
MIT License | MIT License |
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ipme
surface_normal_uncertainty
-
Non official colab to create normal maps using "Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation" from baegwangbin
I needed normal maps for my movie and I saw in the new ControlNet update that they used https://github.com/baegwangbin/surface_normal_uncertainty to make normals which gave me better results than previous methods. So I decided to make a colab to process all my images because I didn't find how to do it in Automatic 1111.
What are some alternatives?
EOmaps - A library to create interactive maps of geographical datasets
2dimageto3dmodel - We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
deep-kernel-transfer - Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
fortuna - A Library for Uncertainty Quantification.
uncertainty-toolbox - Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
IGR - Implicit Geometric Regularization for Learning Shapes
DIML - [ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching
neural-deferred-shading - Multi-View Mesh Reconstruction with Neural Deferred Shading (CVPR 2022)
calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)