How do I fix the blurred image generation problem in a VAE

Question

With the help of Python programming, can you tell me How do I fix the blurred image generation problem in a VAE?

Answer 1

To fix the blurred image generation problem in a Variational Autoencoder (VAE), you can follow the following steps:

• Use a more expressive decoder: Increase the complexity of the decoder network.
• Adopt a perceptual loss: Compare high-level features instead of pixel-wise differences.
• Increase latent space capacity: Use a higher-dimensional latent space to capture more detail.
• Use a beta-VAE: Adjust the KL divergence weight (β) for better trade-off between reconstruction and regularization.

Here is the code snippet you can refer to:

In the above code, we are using the following:

• Improved Decoder: Add more layers and neurons.
• Perceptual Loss: Use high-level features instead of pixel-wise losses.
• Latent Space: Increase dimensionality to capture finer details.
• Beta Adjustment: Tune β to balance regularization and detail.

Hence, this approach reduces blurriness and improves generated image quality.