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

Exquisite demand exists for customizing the pretrained large text-to-imagemodel, $\textit{e.g.}$, Stable Diffusion, to generate innovative concepts, suchas the users themselves. However, the newly-added concept from previouscustomization methods often shows weaker combination abilities than theoriginal ones even given several images during training. We thus propose a newpersonalization method that allows for the seamless integration of a uniqueindividual into the pre-trained diffusion model using just $\textbf{one facialphotograph}$ and only $\textbf{1024 learnable parameters}$ under $\textbf{3minutes}$. So as we can effortlessly generate stunning images of this person inany pose or position, interacting with anyone and doing anything imaginablefrom text prompts. To achieve this, we first analyze and build a well-definedceleb basis from the embedding space of the pre-trained large text encoder.Then, given one facial photo as the target identity, we generate its ownembedding by optimizing the weight of this basis and locking all otherparameters. Empowered by the proposed celeb basis, the new identity in ourcustomized model showcases a better concept combination ability than previouspersonalization methods. Besides, our model can also learn several newidentities at once and interact with each other where the previouscustomization model fails to. The code will be released.

Inserting Anybody in Diffusion Models via Celeb Basis