[D] Is the GAN architecture currently old-fashioned?

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning

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  • joliGEN

    Generative AI Image Toolset with GANs and Diffusion for Real-World Applications

  • We use https://github.com/jolibrain/joliGAN which is a lib for image2image with additional "semantic" constraints. I.e. when there's a need to conserve labels, physics, anything between the two domains. This lib aggregates and improves on existing works.

  • projected-gan

    [NeurIPS'21] Projected GANs Converge Faster

  • If you are looking for more traditional noise -> xxx GANs, go for https://github.com/autonomousvision/projected_gan/. Another recent work is https://github.com/nupurkmr9/vision-aided-gan.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • vision-aided-gan

    Ensembling Off-the-shelf Models for GAN Training (CVPR 2022 Oral)

  • If you are looking for more traditional noise -> xxx GANs, go for https://github.com/autonomousvision/projected_gan/. Another recent work is https://github.com/nupurkmr9/vision-aided-gan.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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