---
title: "Hybrid Mesh-Gaussian Representation for Efficient Indoor Scene Reconstruction"
authors:
  - "Binxiao Huang"
  - "Zhihao Li"
  - "Shiyong Liu"
  - "Xiao Tang"
  - "Jiajun Tang"
  - "Jiaqi Lin"
  - "Yuxin Cheng"
  - "Zhenyu Chen"
  - "Xiaofei Wu"
  - "Ngai Wong"
doi: "10.24963/ijcai.2025/128"
url: "https://ijcai.org/proceedings/2025/128"
pdf: "https://ijcai.org/proceedings/2025/0128.pdf"
venue: "Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"
year: 2025
pages: "1143-1151"
track: "Main Track"
keywords:
  - "Computer Vision: CV: Representation learning"
  - "Computer Vision: CV: 3D computer vision"
---

# Hybrid Mesh-Gaussian Representation for Efficient Indoor Scene Reconstruction

Binxiao Huang, Zhihao Li, Shiyong Liu, Xiao Tang, Jiajun Tang, Jiaqi Lin, Yuxin Cheng, Zhenyu Chen, Xiaofei Wu, Ngai Wong

*Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence*, pages 1143-1151. DOI: [10.24963/ijcai.2025/128](https://doi.org/10.24963/ijcai.2025/128)

## Abstract

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations accurately, leading to inefficiencies in rendering speed. To address this challenge, we introduce a hybrid representation for indoor scenes that combines 3DGS with textured meshes. Our approach uses textured meshes to handle texture-rich flat areas, while retaining Gaussians to model intricate geometries. The proposed method begins by pruning and refining the extracted mesh to eliminate geometrically complex regions. We then employ a joint optimization for 3DGS and mesh, incorporating a warm-up strategy and transmittance-aware supervision to balance their contributions seamlessly.Extensive experiments demonstrate that the hybrid representation maintains comparable rendering quality and achieves superior frames per second FPS with fewer Gaussian primitives.