Efficient Part-level 3D Object Generation via Dual Volume Packing

TL;DR

This paper introduces a novel end-to-end framework for part-level 3D object generation from a single image, utilizing dual volume packing to improve quality, diversity, and part manipulation.

Contribution

It proposes a dual volume packing strategy enabling flexible, high-quality part-level 3D object generation with arbitrary parts from a single image.

Findings

Achieves better quality than previous methods

Generates diverse and semantically meaningful parts

Demonstrates strong generalization capabilities

Abstract

Recent progress in 3D object generation has greatly improved both the quality and efficiency. However, most existing methods generate a single mesh with all parts fused together, which limits the ability to edit or manipulate individual parts. A key challenge is that different objects may have a varying number of parts. To address this, we propose a new end-to-end framework for part-level 3D object generation. Given a single input image, our method generates high-quality 3D objects with an arbitrary number of complete and semantically meaningful parts. We introduce a dual volume packing strategy that organizes all parts into two complementary volumes, allowing for the creation of complete and interleaved parts that assemble into the final object. Experiments show that our model achieves better quality, diversity, and generalization than previous image-based part-level generation methods.