---
license: bigscience-openrail-m
base_model:
- MiniMaxAI/MiniMax-H3-Image
---

**NOTE Encoder was Frozen Using this VAE for Training should not effect outcome**

## Overview

This repository contains evaluation results for a **MiniMax Image HDR VAE (High Dynamic Range Variational Autoencoder)** designed for MiniMax-H3 image reconstruction and enhancement workflows.

The HDR VAE is evaluated against the **BASE MiniMax Image VAE** using a multi-domain reconstruction analysis covering:

* perceptual similarity
* structural energy enhancement
* color distribution changes
* saturation enhancement
* sharpness and high-frequency detail
* channel-level color differences

The objective is not only to measure pixel reconstruction accuracy, but to evaluate how the VAE enhances image characteristics through the encode/decode pipeline.

### Image Enhancement

Measured through reconstruction comparisons:

* RGB pixel deviation
* saturation changes
* gradient energy
* sharpness retention
* contrast gain
* high-frequency energy
* perceptual color difference (DeltaE)

These evaluate how reconstruction changes image detail, color intensity, sharpness, and structural information.

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# Results Summary

## BASE MiniMax Image VAE vs HDR VAE

| Metric                        | BASE MiniMax VAE | HDR VAE |
| ----------------------------- | ---------------: | ------: |
| PSNR ↑                        | **32.4389** | 28.4966 |
| SSIM ↑                        | 0.87133 | **0.87810** |
| RGB MAE ↓                     | **0.015623** | 0.028214 |
| Saturation MAE ↓              | **0.034885** | 0.091786 |
| Gradient Energy Retention     | 0.98014 | **1.05029** |
| Sharpness Retention           | **0.96952** | 0.91151 |
| Contrast Retention            | 1.01329 | 1.00179 |
| High-Frequency Retention      | 0.96159 | **1.04110** |
| DeltaE ↓                      | **2.7502** | 7.0100 |

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# Interpretation

The **BASE MiniMax Image VAE** achieves lower pixel reconstruction error and DeltaE, indicating closer numerical agreement with the original input.

The **HDR VAE** demonstrates a different reconstruction profile:

* increased gradient energy
* increased high-frequency energy
* higher structural similarity
* stronger saturation changes
* enhancement-oriented reconstruction behavior

The HDR VAE behaves as an enhancement-oriented reconstruction operator rather than a pixel-preservation model, producing measurable changes to image characteristics during reconstruction.

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# Design Goal

The HDR VAE is designed to improve image characteristics that standard VAEs commonly soften or reduce:

* fine texture
* high-frequency detail
* local contrast
* color variation
* edge definition
* perceived sharpness

Rather than optimizing only for pixel-level similarity, the HDR VAE emphasizes image enhancement through decoder fine-tuning.

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# Conclusion

The evaluation demonstrates two different reconstruction profiles:

**BASE MiniMax Image VAE**

* lower PSNR error
* lower RGB reconstruction error
* lower DeltaE
* stronger numerical color preservation
* more faithful pixel reconstruction

**HDR MiniMax Image VAE**

* higher SSIM
* increased gradient energy
* increased high-frequency energy
* enhancement-oriented reconstruction
* greater image characteristic variation

The HDR VAE provides an enhancement-oriented reconstruction profile for users seeking increased structural information, richer image characteristics, and enhanced visual detail rather than strict pixel-perfect reconstruction.