HIVE-3D: Hierarchical Voxel Enhancement for High-Quality 3D Scene Generation

2026-07-15

AI Summary

This work addresses the limitations of existing single-image 3D scene generation methods, which often rely on low-resolution representations and struggle to reconstruct high-fidelity, complete scenes. To overcome this, the authors propose a hierarchical voxel-enhanced framework for high-fidelity 3D scene synthesis. Given an input image, the method first segments it and leverages an attention mechanism to retrieve and align corresponding 2D–3D components, constructing a hierarchical component tree. It then performs coarse-to-fine voxel super-resolution reconstruction, generating high-resolution 3D scenes while preserving both geometric and semantic consistency at the component level. Extensive evaluations demonstrate that the proposed approach significantly outperforms current state-of-the-art methods across multiple metrics, achieving superior performance in 3D scene generation quality.

Abstract

Recently, a line of works can generate impressive 3D objects from a single image, but they are limited by restricted representation resolution, making them unsuitable for 3D scene generation. In this work, we introduce HIVE-3D, a novel method for high-quality 3D scene generation based on hierarchical voxel enhancement framework. Specifically, given a single scene image as input, we first produce a coarse initial scene, then introduce image segmentation and attention-based retrieval to align 2D image components with 3D scene components. Subsequently, we organize these scene relations into a hierarchical component tree, where nodes closer to the leaves denote finer-grained components. Finally, we propose a voxel super-resolution model that generates refined voxels for the target instance while maintaining strong consistency with the coarse voxels. Equipped with this model, we perform coarse-to-fine hierarchical super-resolution on images and voxels for each component, producing a high-resolution and high-quality 3D scene. Extensive experiments demonstrate that our method significantly outperforms previous approaches, achieving state-of-the-art performance.

Problem

• 3D scene generation
• single image
• representation resolution
• high-quality 3D
• voxel resolution

Innovation

• hierarchical voxel enhancement
• 3D scene generation
• voxel super-resolution
• attention-based retrieval
• coarse-to-fine reconstruction