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

We introduce DreamPaint, a framework to intelligently inpaint any e-commerceproduct on any user-provided context image. The context image can be, forexample, the user's own image for virtual try-on of clothes from the e-commercecatalog on themselves, the user's room image for virtual try-on of a piece offurniture from the e-commerce catalog in their room, etc. As opposed toprevious augmented-reality (AR)-based virtual try-on methods, DreamPaint doesnot use, nor does it require, 3D modeling of neither the e-commerce product northe user context. Instead, it directly uses 2D images of the product asavailable in product catalog database, and a 2D picture of the context, forexample taken from the user's phone camera. The method relies on few-shot finetuning a pre-trained diffusion model with the masked latents (e.g., MaskedDreamBooth) of the catalog images per item, whose weights are then loaded on apre-trained inpainting module that is capable of preserving the characteristicsof the context image. DreamPaint allows to preserve both the product image andthe context (environment/user) image without requiring text guidance todescribe the missing part (product/context). DreamPaint also allows tointelligently infer the best 3D angle of the product to place at the desiredlocation on the user context, even if that angle was previously unseen in theproduct's reference 2D images. We compare our results against both text-guidedand image-guided inpainting modules and show that DreamPaint yields superiorperformance in both subjective human study and quantitative metrics.

DreamPaint: Few-Shot Inpainting of E-Commerce Items for Virtual Try-On without 3D Modeling