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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 9

Indoor scene 3D reconstruction method combining plane constraints and Kolmogorov-Arnold network

Jia Di1,2
Meng Xiaohua1
Cheng Shuo1
Xu Chi1
Liu Yang1
Song Huilun1
1. Ordos Institute of Liaoning Technical University, Ordos 017000, China
2. School of Electronic & Information Engineering, Liaoning Technical University, Huludao 125105, China
DOI: 10.19734/j.issn.1001-3695.2025.01.0009

Abstract

To address the challenges of weak texture areas in indoor 3D reconstruction and the limited ability to express complex scenes, this paper proposed an indoor 3D reconstruction network, KAN-PlaneNet, which combined a plane constraint optimization module and a KAN color branch module. The network, based on Neural Radiance Fields (NeRF) , introduced the KAN module and color attribute inputs in the color branch to enhance the detail expression of complex scenes. In addition, by introducing a plane constraint optimization module, we enforced vertical alignment between wall and floor regions. We defined a learnable wall normal vector nw to constrain the normal direction of surface points on the wall to be parallel or orthogonal to nw. For indoor object regions, we applied a constraint requiring the cosine similarity between the normal direction of the region and the floor normal to be greater than 0.95, thus enforcing parallelism. Experimental results show that the method outperforms existing 3D supervised methods on the ScanNet dataset. Compared to the VolSDF method, the overall evaluation metrics improve by an average of 0.356, validating its superiority.

Foundation Support

国家自然科学基金资助项目(61601213)
辽宁工程技术大学鄂尔多斯研究院校地科技合作培育项目(YJY-XD-2023-003)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.01.0009
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 9

Publish History

[2025-04-29] Accepted Paper

Cite This Article

贾迪, 孟晓华, 程硕, 等. 结合平面约束与Kolmogorov-Arnold网络的室内场景三维重建方法 [J]. 计算机应用研究, 2025, 42 (9). (2025-04-29). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0009. (Jia Di, Meng Xiaohua, Cheng Shuo, et al. Indoor scene 3D reconstruction method combining plane constraints and Kolmogorov-Arnold network [J]. Application Research of Computers, 2025, 42 (9). (2025-04-29). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0009. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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