Accuracy and Fidelity Comparison of Luna and DALL-E 2 Diffusion-Based Image Generation Systems
This work provides a comparative analysis for researchers and practitioners in AI image generation, but it is incremental as it evaluates existing systems without introducing new methods.
The study compared the accuracy and fidelity of two diffusion-based image generation systems, DALL-E 2 and Luna, finding that DALL-E 2 significantly outperformed Luna in both alignment and fidelity.
We qualitatively examine the accuracy and fidelity between two diffusion-based image generation systems, namely DALL-E 2 and Luna, which have massive differences in training datasets, algorithmic approaches, prompt resolvement, and output upscaling. The methodology used is a qualitative benchmark created by Saharia et al. and in our research we conclude that DALL-E 2 significantly edges Luna in both alignment and fidelity comparisons.