contrastive-reconstruction VS mmselfsup

Compare contrastive-reconstruction vs mmselfsup and see what are their differences.

contrastive-reconstruction

Tensorflow-keras implementation for Contrastive Reconstruction (ConRec) : a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reconstruction loss. (by bayer-science-for-a-better-life)
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contrastive-reconstruction mmselfsup
1 5
13 3,169
- 0.0%
10.0 5.3
almost 3 years ago over 1 year ago
Python Python
GNU General Public License v3.0 only Apache License 2.0
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.
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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.

contrastive-reconstruction

Posts with mentions or reviews of contrastive-reconstruction. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-15.

mmselfsup

Posts with mentions or reviews of mmselfsup. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-21.

What are some alternatives?

When comparing contrastive-reconstruction and mmselfsup you can also consider the following projects:

MAGIST-Algorithm - Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta

Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]

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

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

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

anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

vissl - VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.

self_supervised - Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks.

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

animessl - Train vision models with vissl + illustrated images

mmpretrain - OpenMMLab Pre-training Toolbox and Benchmark

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