DIML VS surface_normal_uncertainty

Compare DIML vs surface_normal_uncertainty and see what are their differences.

DIML

[ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching (by wl-zhao)
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DIML surface_normal_uncertainty
1 1
83 196
- -
5.2 10.0
over 2 years ago over 1 year ago
Python Python
- MIT License
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DIML

Posts with mentions or reviews of DIML. 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 DIML and surface_normal_uncertainty you can also consider the following projects:

pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

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.

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

fortuna - A Library for Uncertainty Quantification.

XVFI - [ICCV 2021, Oral 3%] Official repository of XVFI

IGR - Implicit Geometric Regularization for Learning Shapes

pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

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

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)