riejohnson/cfg-gan
CFG-GAN: Composite functional gradient learning of generative adversarial models
This project helps researchers working in generative AI to train and evaluate models that create new images. You can input existing image datasets and train a generative model using the xICFG algorithm. The output is a model capable of generating novel images, along with evaluations of their quality. It's intended for AI researchers or machine learning engineers exploring new image generation techniques.
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Use this if you are an AI researcher or machine learning engineer looking to implement and experiment with the xICFG algorithm for image generation in a C++ environment.
Not ideal if you prefer a Python-based workflow or do not have access to a high-memory CUDA-capable GPU, as a PyTorch version is available for those needs.
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15
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Language
C++
License
GPL-3.0
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Last pushed
Jul 09, 2020
Commits (30d)
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