Paper
12 October 2022 Single image 3D scene reconstruction based on ShapeNet models
Xueyang Chen, Yifan Ren, Yaoxu Song
Author Affiliations +
Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 1234213 (2022) https://doi.org/10.1117/12.2645274
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China
Abstract
The 3D scene reconstruction task is the basis for implementing mixed reality, but traditional single-image scene reconstruction algorithms are difficult to generate regularized models. It is believed that this situation is caused by a lack of prior knowledge, so we try to introduce the model collection ShapeNet 1 to solve this problem. Besides, our approach incorporates traditional model generation algorithms. The predicted artificial indoor objects as indicators will match models in ShapeNet. The refined models selected from ShapeNet will then replace the rough ones to produce the final 3D scene. These selected models from the model library will greatly improve the aesthetics of the reconstructed 3D scene. We test our method on the NYU-v2 2 dataset and achieve pleasing results. Our project is publicly available at https://sjtu-cv- 2021.github.io/Single-Image-3D-Reconstruction-Based-On-ShapeNet.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xueyang Chen, Yifan Ren, and Yaoxu Song "Single image 3D scene reconstruction based on ShapeNet models", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 1234213 (12 October 2022); https://doi.org/10.1117/12.2645274
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
3D modeling

3D image reconstruction

3D image processing

Reconstruction algorithms

Performance modeling

Image segmentation

Statistical modeling

Back to Top