neural-deferred-shading VS surface_normal_uncertainty

Compare neural-deferred-shading vs surface_normal_uncertainty and see what are their differences.

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neural-deferred-shading surface_normal_uncertainty
1 1
239 196
5.4% -
4.6 10.0
2 months ago over 1 year ago
Python Python
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

neural-deferred-shading

Posts with mentions or reviews of neural-deferred-shading. We have used some of these posts to build our list of alternatives and similar projects.

surface_normal_uncertainty

Posts with mentions or reviews of surface_normal_uncertainty. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing neural-deferred-shading and surface_normal_uncertainty you can also consider the following projects:

ECON - [CVPR'23, Highlight] ECON: Explicit Clothed humans Optimized via Normal integration

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.

GAN2Shape - Code for GAN2Shape (ICLR2021 oral)

fortuna - A Library for Uncertainty Quantification.

MICA - MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]

IGR - Implicit Geometric Regularization for Learning Shapes

3d-transforms - 3D Transforms is a library to easily work with 3D data and make 3D transformations. This library originally started as a few functions here and there for my own work which I then turned into a library.

ipme - An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".

DIML - [ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching

BlenderNeRF - Easy NeRF synthetic dataset creation within Blender

calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)