arXiv Computer Vision

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

arXiv AI
Aug 7

WorldClaw: Agentic 3D Open-World Generation at Scale

arXiv:2608. 05248v1 Announce Type: new Abstract: Generating large-scale, freely explorable 3D worlds from open-ended text remains challenging because a system must jointly maintain global spatial coherence, rich local content, and explicit assets suitable for downstream editing and reuse.

By Chunchao Guo, Jinpeng Li, Yang Li, Zilong Huang
arXiv Computer Vision
Oct 15

Holi-Spatial 360: Generative Reconstruction from Sparse Panoramas for Spatial Rendering and Intelligence

arXiv:2610.19502v1 Announce Type: new Abstract: Spatial intelligence requires scalable 3D environments that are both photorealistic and semantically grounded, yet existing indoor datasets are dominat...

By Yuanyuan Gao, Zhirui Liu, Yuning Gong, Yifei Liu, Yifan Zhan, Kuixuan Jiao, Xiaolong Zhou, Yifan Yang, Hongjie Zhang, Xue Yang, Dan Xu, Zhihang Zhong
arXiv Computer Vision
Oct 7

Building Rome from a Single Image

arXiv:2610.08790v1 Announce Type: new Abstract: Single-image scene generation aims to produce a complete 3D scene mesh from a single image, including surfaces the camera did not observe. While pretra...

By Jiraphon Yenphraphai, Fang Li, Tianshuo Xu, Depu Meng, Quentin Herau, Yihan Hu, Raymond A. Yeh, Wei Zhan
Hugging Face Trending Papers
Oct 6

Building Rome from a Single Image

Single-image scene generation aims to produce a complete 3D scene mesh from a single image, including surfaces the camera did not observe. While pretrained 3D object generators encode a strong shape p...

arXiv Computation and Language
Sep 1

PlanCraft: Sketch, Refine, and Furnish for Architect-Inspired Progressive 3D Residential Scene Generation

PlanCraft introduces a progressive approach to 3D residential scene generation that mirrors how architects design: starting with rough sketches and refining them over time. It leverages a large dataset of real floor plans to train a SketchPlan module that generates partial sketches at various completion levels, a PlanCraft‑Diff module that sharpens these sketches into precise vector floor plans, and a PlanCraft‑Agent that furnishes rooms within the established spatial contract. The method outperforms existing 2D and 3D baselines, achieving a 61.1% lower FID and a 15‑point lead in expert‑rated spatial rationality, even with only 25% sketch completion.

By Pengyu Zeng, Yuqin Dai, Jun Yin, Ziyang Han, Ng Cheuk Hei, Jing Zhong, Chaoyang Shi, ZhanXiang Jin, Maowei Jiang, Shuai Lu