DragGAN VS BMSG-GAN

Compare DragGAN vs BMSG-GAN and see what are their differences.

BMSG-GAN

[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation (by akanimax)
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DragGAN BMSG-GAN
1 1
89 629
- -
7.1 10.0
12 months ago almost 2 years ago
Python Python
MIT License MIT License
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.

DragGAN

Posts with mentions or reviews of DragGAN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-02.

BMSG-GAN

Posts with mentions or reviews of BMSG-GAN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-16.

What are some alternatives?

When comparing DragGAN and BMSG-GAN you can also consider the following projects:

DragGAN - Official Code for DragGAN (SIGGRAPH 2023)

concept-ablation - Ablating Concepts in Text-to-Image Diffusion Models (ICCV 2023)

neural_networks

News-Sense - A Streamlit app based on Python that fetches top news articles from the News API, generates a summary of each article using the OpenAI GPT-3 model, analyzes the sentiment of the article using the NLTK library, and classifies the article into different categories based on keywords.

neuro-symbolic-sudoku-solver - ⚙️ Solving sudoku using Deep Reinforcement learning in combination with powerful symbolic representations.

dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).