PASS VS Unsupervised-Semantic-Segmentation

Compare PASS vs Unsupervised-Semantic-Segmentation and see what are their differences.

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PASS Unsupervised-Semantic-Segmentation
4 1
257 386
- -
0.0 1.8
almost 2 years ago almost 2 years ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

PASS

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

Unsupervised-Semantic-Segmentation

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

What are some alternatives?

When comparing PASS and Unsupervised-Semantic-Segmentation you can also consider the following projects:

auth-source-pass - Integrate Emacs' auth-source with password-store

mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark

unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)

Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

DA-RetinaNet - Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'

self-supervised - Whitening for Self-Supervised Representation Learning | Official repository

solo-learn - solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

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

DiffCSE - Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"

lightly - A python library for self-supervised learning on images.