Dr. Lei Zhu Profile

Dr. Lei Zhu

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Proceedings Article | 7 March 2024 Paper

Research on point cloud scene parsing method based on M2F

Feng Yin, Juan Li, Lei Zhu, Wenwu Wang

Proceedings Volume 13086, 130860N (2024) https://doi.org/10.1117/12.3005246

KEYWORDS: Point clouds

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Semantic segmentation aims to divide a scene into regions with different semantic categories. The prevalent technique in scene semantic segmentation is denoted as pixel-based segmentation, whereby classifications are assigned to singular points. However, the principles used to make predictions through these methods exhibit significant differences from the way in which a scene would be processed through human vision. When encountering new scenes, humans initially concentrate on each instance within the three-dimensional scene, rather than individual pixels. Inspired by M2F, a popular instance-based architecture proposed for 2D segmentation, we propose a 3D semantic segmentation algorithm based on M2F. It departs from the common practice of per-pixel classification in point cloud semantic segmentation. Instead, we first predict the instance mask and then assign labels to each point within the corresponding instance. In our experiments, the scene was divided into regions, and each region was treated as a complete entity and associated with a single global class label prediction. Thus, the pixel-wise classification problem in existing 3D semantic segmentation was transformed into a region-based classification problem in a 3D scene. The experiment conducted on the popular public database S3DIS illustrates that the proposed method achieves 68.5% mIoU / 74.3 mAcc, outperforming other competing approaches with certain margin.

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