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 present DiffInDScene, a novel framework for tackling the problem ofhigh-quality 3D indoor scene generation, which is challenging due to thecomplexity and diversity of the indoor scene geometry. Although diffusion-basedgenerative models have previously demonstrated impressive performance in imagegeneration and object-level 3D generation, they have not yet been applied toroom-level 3D generation due to their computationally intensive costs. InDiffInDScene, we propose a cascaded 3D diffusion pipeline that is efficient andpossesses strong generative performance for Truncated Signed Distance Function(TSDF). The whole pipeline is designed to run on a sparse occupancy space in acoarse-to-fine fashion. Inspired by KinectFusion's incremental alignment andfusion of local TSDF volumes, we propose a diffusion-based SDF fusion approachthat iteratively diffuses and fuses local TSDF volumes, facilitating thegeneration of an entire room environment. The generated results demonstratethat our work is capable to achieve high-quality room generation directly inthree-dimensional space, starting from scratch. In addition to the scenegeneration, the final part of DiffInDScene can be used as a post-processingmodule to refine the 3D reconstruction results from multi-view stereo.According to the user study, the mesh quality generated by our DiffInDScene caneven outperform the ground truth mesh provided by ScanNet. Please visit ourproject page for the latest progress and demonstrations:https://github.com/AkiraHero/diffindscene.

DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene Generation