NavCrafter: Exploring 3D Scenes from a Single Image
Hongbo Duan, Peiyu Zhuang, Yi Liu, Zhengyang Zhang, Yuxin Zhang, Pengting Luo, Fangming Liu, Xueqian Wang

TL;DR
NavCrafter is a novel framework that synthesizes controllable 3D scenes from a single image, enabling high-quality novel-view video generation with improved 3D reconstruction.
Contribution
It introduces a multi-stage camera control mechanism, a collision-aware trajectory planner, and an enhanced 3D Gaussian Splatting pipeline for better 3D scene synthesis.
Findings
Achieves state-of-the-art novel-view synthesis under large viewpoint shifts.
Substantially improves 3D reconstruction fidelity.
Demonstrates effective scene coverage expansion from a single image.
Abstract
Creating flexible 3D scenes from a single image is vital when direct 3D data acquisition is costly or impractical. We introduce NavCrafter, a novel framework that explores 3D scenes from a single image by synthesizing novel-view video sequences with camera controllability and temporal-spatial consistency. NavCrafter leverages video diffusion models to capture rich 3D priors and adopts a geometry-aware expansion strategy to progressively extend scene coverage. To enable controllable multi-view synthesis, we introduce a multi-stage camera control mechanism that conditions diffusion models with diverse trajectories via dual-branch camera injection and attention modulation. We further propose a collision-aware camera trajectory planner and an enhanced 3D Gaussian Splatting (3DGS) pipeline with depth-aligned supervision, structural regularization and refinement. Extensive experiments…
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