Multi-resolution encoding improves Generative AI by capturing both fine-grained and high-level features across multiple scales, enhancing detail preservation and overall output quality.
Here is the code snippet you can refer to:

In the above code we are using the following key points:
- Uses Multi-Scale Convolutions to capture details at different resolutions.
- Includes Downsampling and Upsampling Layers to enhance feature richness.
- Preserves Fine-Grained Features by concatenating multi-resolution outputs.
- Improves Generative Quality by combining coarse and detailed representations.
- Optimized for High-Resolution Outputs in Generative AI models.
Hence, multi-resolution encoding enhances Generative AI by integrating high- and low-frequency details, resulting in more detailed and realistic outputs.