anantzoid/Conditional-PixelCNN-decoder
A Tensorflow implementation of Gated PixelCNN for conditional image generation based on class labels or latent representations.
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This repository implements the Gated PixelCNN architecture from the paper ‘Conditional Image Generation with PixelCNN Decoders’. The model uses gated convolutions to remember context and model complex interactions for autoregressive image generation. It supports unconditional generation, class-conditional generation, and can serve as a decoder replacement for deconvolution in autoencoders and GANs. The architecture includes vertical stacks with masking to handle blind spots and residual connections to improve performance.
Frequently asked
- What is anantzoid/Conditional-PixelCNN-decoder?
- A Tensorflow implementation of Gated PixelCNN for conditional image generation based on class labels or latent representations.
- Is Conditional-PixelCNN-decoder open source?
- Yes — anantzoid/Conditional-PixelCNN-decoder is an open-source project tracked on heatdrop.
- What language is Conditional-PixelCNN-decoder written in?
- anantzoid/Conditional-PixelCNN-decoder is primarily written in Python.
- How popular is Conditional-PixelCNN-decoder?
- anantzoid/Conditional-PixelCNN-decoder has 479 stars on GitHub.
- Where can I find Conditional-PixelCNN-decoder?
- anantzoid/Conditional-PixelCNN-decoder is on GitHub at https://github.com/anantzoid/Conditional-PixelCNN-decoder.