WonderZoom: Multi-Scale 3D World Generation

Jin Cao, Hong-Xing Yu, Jiajun Wu

Keywords: Multi-scale generation, 3D world generation

TL;DR: WonderZoom generates multi-scale 3D worlds from a single image, enabling users to zoom in and synthesize new fine-scale 3D content on demand.

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 outperforms state-of-the-art video and 3D models in both quality and alignment, enabling multi-scale 3D world creation from a single image. We show video results and an interactive viewer of generated multi-scale 3D worlds in https://wonderzoom.github.io/.

Primary Area: applications to computer vision, audio, language, and other modalities

Submission Number: 3585