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StyleGAN-nada Alternatives
Similar projects and alternatives to StyleGAN-nada
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stylegan2-pytorch
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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stylegan3-fun
Modifications of the official PyTorch implementation of StyleGAN3. Let's easily generate images and videos with StyleGAN2/2-ADA/3!
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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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deep-photo-styletransfer
Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better StyleGAN-nada alternative or higher similarity.
StyleGAN-nada reviews and mentions
Posts with mentions or reviews of StyleGAN-nada.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-19.
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Artists Tomorrow
Here's a paper about adding the ability to guide outputs with text a full year before Stable Diffusion was published.
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StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
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[R][P] Gradio Web demo for StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators (SIGGRAPH 2022)
project page: https://stylegan-nada.github.io/
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The Danny AI of your dreams
Sooo I retrained the FFHQ model to be Danny using StyleGAN-NADA via this Colab notebook.
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I made a VFX face filter thing that might be of interest to you guys (it runs in the browser without sending anything to a server and is quite fast)
Haha thanks for trying it out :) It was actually really challenging to get it working (especially all in the browser without processing on a server). A lot of help came from stylegan-nada https://github.com/rinongal/StyleGAN-nada (and a custom lightweight model basically distilling pairs from it and ffhq).
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[D] StyleGAN3: Overview, Tutorial, and Pre-Trained Model
As for usage on non-face images most of NVidia's pre-trained models were face based (animal, humans, and paintings). Which was the aim of releasing our WikiArt model so the community would have something that could generate a greater variety of images. However these models are still constrained to the dataset that they were trained on. So without some tricks you can't generate "novel" images (like mashups of different objects)
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[D] What are some cool projects for generating art?
I think the directional loss concepts in https://github.com/rinongal/StyleGAN-nada have real potential for artistic work, as they can go beyond the filter and paint effects that traditional style transfer applies well, while maintaining recognisable equivalency between the resulting images.
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[R] NVIDIA and Tel Aviv Researchers Propose ‘StyleGAN-NADA’, A Text-Driven Method That Converts a Pre-Trained AI Generator to New Domains Using Only a Textual Prompt and No Training Data
5 Min Read | Paper | Project | Code
- Arquitectura colonial Argentina (Generado por IA)
- StyleGAN-NADA: Clip-Guided Domain Adaptation of Image Generators
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A note from our sponsor - SaaSHub
www.saashub.com | 25 Apr 2024
Stats
Basic StyleGAN-nada repo stats
14
1,141
0.0
over 1 year ago
rinongal/StyleGAN-nada is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of StyleGAN-nada is Python.
Popular Comparisons
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- StyleGAN-nada VS deep-photo-styletransfer
- StyleGAN-nada VS prompt-to-prompt
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