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

In this work, we investigate the problem of creating high-fidelity 3D contentfrom only a single image. This is inherently challenging: it essentiallyinvolves estimating the underlying 3D geometry while simultaneouslyhallucinating unseen textures. To address this challenge, we leverage priorknowledge from a well-trained 2D diffusion model to act as 3D-aware supervisionfor 3D creation. Our approach, Make-It-3D, employs a two-stage optimizationpipeline: the first stage optimizes a neural radiance field by incorporatingconstraints from the reference image at the frontal view and diffusion prior atnovel views; the second stage transforms the coarse model into textured pointclouds and further elevates the realism with diffusion prior while leveragingthe high-quality textures from the reference image. Extensive experimentsdemonstrate that our method outperforms prior works by a large margin,resulting in faithful reconstructions and impressive visual quality. Our methodpresents the first attempt to achieve high-quality 3D creation from a singleimage for general objects and enables various applications such as text-to-3Dcreation and texture editing.

Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior