WonderZoom: Multi-Scale 3D World Generation
Jin Cao, Hong-Xing Yu, Jiajun Wu

TL;DR
WonderZoom introduces a multi-scale 3D scene generation method from a single image, using scale-adaptive surfels and progressive detail synthesis to produce coherent scenes at varying granularities, outperforming existing models.
Contribution
It proposes a novel scale-aware 3D representation and synthesis approach enabling multi-scale scene generation from a single image, addressing limitations of prior single-scale models.
Findings
Outperforms state-of-the-art models in quality and alignment
Enables interactive zooming and detail synthesis in 3D scenes
Successfully generates scenes with details from landscapes to microscopic features
Abstract
We present WonderZoom, a novel approach to generating 3D scenes with contents across multiple spatial scales from a single image. Existing 3D world generation models remain limited to single-scale synthesis and cannot produce coherent scene contents at varying granularities. The fundamental challenge is the lack of a scale-aware 3D representation capable of generating and rendering content with largely different spatial sizes. WonderZoom addresses this through two key innovations: (1) scale-adaptive Gaussian surfels for generating and real-time rendering of multi-scale 3D scenes, and (2) a progressive detail synthesizer that iteratively generates finer-scale 3D contents. Our approach enables users to "zoom into" a 3D region and auto-regressively synthesize previously non-existent fine details from landscapes to microscopic features. Experiments demonstrate that WonderZoom significantly…
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Taxonomy
Topics3D Shape Modeling and Analysis · Generative Adversarial Networks and Image Synthesis · Advanced Vision and Imaging
