Skip to content
NewA calmer, faster ZeroHour

To See a World in a Living Context: Unified Indoor-Outdoor Urban World Generation

Hugging Face daily papersby Xiaobin Huang, Zilong Huang, Yang Luo ()1 min read1 · 1 read
AI summary · glm-5.3-flashSummaries by Vani AI

Researchers introduce HoloWorld, a unified text-driven framework generating coherent indoor-outdoor 3D urban worlds, improving average AQS over SOTA by 7.68%.

HoloWorld is a text-driven 3D generation framework that unifies indoor and outdoor urban world generation using a continuously updated cross-scale world context. It autoregressively generates urban exteriors with consistent spatial organization, grounded in 3D building instances and footprints, then produces building-specific interiors with geometry-constrained layouts that inherit exterior appearance. The authors claim it is the first framework to unify indoor and outdoor generation within one coherent 3D urban world, reporting a 7.68% average AQS improvement over prior SOTA and the highest average RDR score.

Key facts
  • First framework claimed to unify indoor and outdoor generation in one coherent 3D urban world.
  • Cross-scale context spans city-scale planning down to individual buildings, linking interiors to exteriors.
  • Reports 7.68% average AQS improvement over SOTA plus the highest average RDR score.
Explain this AI news with Vani AIWhat was announced, what is new and why it matters, in a new chat

From the original article

1 min read at huggingface.co

Text-driven 3D generation has advanced rapidly in creating large-scale outdoor environments and detailed indoor scenes, but these domains are usually synthesized independently, lacking the correspondence required for a coherent urban world. We present HoloWorld, a unified indoor-outdoor urban world generation framework built on a continuously updated cross-scale world context.

Hugging Face daily papers

By Xiaobin Huang, Zilong Huang, Yang Luo · huggingface.co

Read the full article at Hugging Face daily papers

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.