# SNAP3D：从单张图像生成可用于装配的物理合理 3D 部件

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-09-11 08:00
- AIHOT 分数：35
- AIHOT 链接：https://aihot.news/items/cmu0nreon0382rox2wzx6mse0
- 原文链接：https://arxiv.org/abs/2609.13146

## AI 摘要

SNAP3D 提出一种物理引导框架，从单张图像生成部件级 3D 资产，解决相邻部件互相穿透、连接无效或受重力坍塌的问题。该方法消除部件间穿透、恢复接触图，并在接触面引入参数化连接件，借助物理仿真反馈优化其位置、朝向与尺寸。作者同时提出基于物理的评测协议，直接检验装配有效性与重力下的稳定性，并通过 3D 打印和真实装配验证结果。

## 正文

Part-aware 3D asset generation enables applications such as editing, articulation, simulation, and fabrication, yet existing methods can generate visually complete individual parts without ensuring that they form a valid physical assembly. Consequently, generated neighboring parts may interpenetrate, lack valid connections, or collapse under gravity. We propose a physics-guided framework for improving single-image part-aware 3D generation with physically compatible geometry and stable connections. Our method resolves inter-part penetration, recovers a contact graph between neighboring parts, and introduces parameterized connectors at their contact surfaces.

Using feedback from physical simulation, we refine connector placement, orientation, and dimensions to improve assembly stability while preserving the generated geometry. We further introduce a physics-based evaluation protocol that complements conventional geometric metrics by directly testing assembly validity and stability under gravity. Experiments comparing against multiple part-aware 3D generators show substantial improvements in physical realizability and stability while maintaining geometric quality. We additionally validate the resulting parts through 3D printing and real-world assembly.