Papers › A Large-Scale Network Construction and Lightweighting Method for Point Cloud Semantic...
A Large-Scale Network Construction and Lightweighting Method for Point Cloud Semantic Segmentation
Jiawei Han; Kaiqi Liu; Wei Li; Guangzhi Chen; Wenguang Wang; Feng Zhang
To significantly enhance the performance of point cloud semantic segmentation, this manuscript presents a novel method for constructing large-scale networks and offers an effective lightweighting technique. First, a latent point feature processing (LPFP) module is utilized to interconnect base networks such as PointNet++ and Point Transformer. This intermediate module serves both as a feature information transfer and a ground truth supervision function. Furthermore, in order to alleviate the increase in computational costs brought by constructing large-scale networks and better adapt to the demand for terminal deployment, a novel point cloud lightweighting method for semantic segmentation network (PCLN) is proposed to compress the network by transferring multidimensional feature information of large-scale networks. Specifically, at different stages of the large-scale network, the structure and attention information of the point features are selectively transferred to guide the compressed network to train in the direction of the large-scale network. This paper also solves the problem of representing global structure information of large-scale point clouds through feature sampling and aggregation. Extensive experiments on public datasets and real-world data demonstrate that the proposed method can significantly improve the performance of different base networks and outperform the state-of-the-art.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Semantic Segmentation | S3DIS Area5 | LPFP(Point Transformer*) | FLOPs | 24.2G | #10 of 61 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | LPFP(Point Transformer*) | Number of params | 31.2M | #10 of 61 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | LPFP(Point Transformer*) | mAcc | 78.7 | #10 of 61 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | LPFP(Point Transformer*) | mIoU | 73.5 | #10 of 61 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | LPFP(Point Transformer*) | oAcc | 92.0 | #10 of 61 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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