English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The field of image synthesis has made great strides in the last couple ofyears. Recent models are capable of generating images with astonishing quality.Fine-grained evaluation of these models on some interesting categories such asfaces is still missing. Here, we conduct a quantitative comparison of threepopular systems including Stable Diffusion, Midjourney, and DALL-E 2 in theirability to generate photorealistic faces in the wild. We find that StableDiffusion generates better faces than the other systems, according to the FIDscore. We also introduce a dataset of generated faces in the wild dubbed GFW,including a total of 15,076 faces. Furthermore, we hope that our study spursfollow-up research in assessing the generative models and improving them. Dataand code are available at data and code, respectively.

Generated Faces in the Wild: Quantitative Comparison of Stable Diffusion, Midjourney and DALL-E 2