<img src="docs/figs/logo.png" align="center" width="30%"> <h3 align="center">LaserMix for Semi-Supervised LiDAR Semantic Segmentation</h3> <a href="https://scholar.google.com/citations?user=-j1j7TkAAAAJ" target='_blank'>Lingdong Kong</a>,  <a href="https://scholar.google.com/citations?user=YUKPVCoAAAAJ" target='_blank'>Jiawei Ren</a>,  <a href="https://scholar.google.com/citations?user=lSDISOcAAAAJ" target='_blank'>Liang Pan</a>,  <a href="https://scholar.google.com/citations?user=lc45xlcAAAAJ" target='_blank'>Ziwei Liu</a> S-Lab, Nanyang Technological University <a href="https://arxiv.org/abs/2207.00026" target='_blank'> <img src="https://img.shields.io/badge/Paper-%F0%9F%93%83-yellow"> </a> <a href="https://ldkong.com/LaserMix" target='_blank'> <img src="https://img.shields.io/badge/Project-%F0%9F%94%97-lightblue"> </a> <a href="https://youtu.be/Xkwa5-dT0g4" target='_blank'> <img src="https://img.shields.io/badge/Demo-%F0%9F%8E%AC-yellow"> </a> <a href="" target='_blank'> <img src="https://img.shields.io/badge/Poster-%F0%9F%93%83-lightblue"> </a> <a href="https://zhuanlan.zhihu.com/p/528689803" target='_blank'> <img src="https://img.shields.io/badge/%E4%B8%AD%E8%AF%91%E7%89%88-%F0%9F%90%BC-yellow"> </a> <a href="" target='_blank'> <img src="https://visitor-badge.laobi.icu/badge?page_id=ldkong1205.LaserMix&left_color=gray&right_color=lightblue"> </a>

About

LaserMix is a semi-supervised learning (SSL) framework designed for LiDAR semantic segmentation. It leverages the strong spatial prior of driving scenes to construct low-variation areas via laser beam mixing, and encourages segmentation models to make confident and consistent predictions before and after mixing.

<img src="docs/figs/laser.png" align="center" width="50%"> Fig. Illustration for laser beam partition based on inclination φ.

Visit our <a href="https://ldkong.com/LaserMix" target='_blank'>project page</a> to explore more details. :red_car:

:books: Citation

If you find this work helpful, please kindly consider citing our papers:

@inproceedings{kong2023lasermix,
    title     = {{LaserMix} for Semi-Supervised {LiDAR} Semantic Segmentation},
    author    = {Kong, Lingdong and Ren, Jiawei and Pan, Liang and Liu, Ziwei},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    pages     = {21705-21715},
    year      = {2023}
}

@article{kong2025multi,
    title     = {Multi-Modal Data-Efficient {3D} Scene Understanding for Autonomous Driving},
    author    = {Kong, Lingdong and Xu, Xiang and Ren, Jiawei and others},
    journal   = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
    volume    = {47},
    number    = {5},
    pages     = {3748-3765},
    year      = {2025}
}

Updates

[2024.05] - Our improved framework, LaserMix++ :rocket:, is avaliable on arXiv.
[2024.01] - The toolkit tailored for The RoboDrive Challenge has been released. :hammer_and_wrench:
[2023.12] - We are hosting The RoboDrive Challenge at ICRA 2024. :blue_car:
[2023.12] - Introducing FRNet, an efficient and effective real-time LiDAR segmentation model that achieves promising semi-supervised learning results on SemanticKITTI and nuScenes. Code and checkpoints are available for downloading.
[2023.03] - Intend to test the robustness of your LiDAR semantic segmentation models? Check our recent work, :robot: Robo3D, a comprehensive suite that enables OoD robustness evaluation of 3D segmentors on our newly established datasets: SemanticKITTI-C, nuScenes-C, and WOD-C.
[2023.03] - LaserMix was selected as a :sparkles: highlight :sparkles: at CVPR 2023 (top 10% of accepted papers).
[2023.02] - LaserMix was accepted to CVPR 2023! :tada:
[2023.02] - LaserMix has been integrated into the MMDetection3D codebase! Check this PR in the dev-1.x branch to know more details. :beers:
[2023.01] - As suggested, we will establish a sequential track taking into account the LiDAR data collection nature in our semi-supervised LiDAR semantic segmentation benchmark. The results will be gradually updated in RESULT.md.
[2022.12] - We support a wider range of LiDAR segmentation backbones, including RangeNet++, SalsaNext, FIDNet, CENet, MinkowskiUNet, Cylinder3D, and SPVCNN, under both fully- and semi-supervised settings. The checkpoints will be available soon!
[2022.12] - The derivation of spatial-prior-based SSL is available here. Take a look! :memo:
[2022.08] - LaserMix achieves 1st place among the semi-supervised semantic segmentation leaderboards of nuScenes, SemanticKITTI, and ScribbleKITTI, based on Paper-with-Code. :bar_chart:
[2022.08] - We provide a video demo for visual comparisons on the SemanticKITTI val set. Take a look!
[2022.07] - Our paper is available on arXiv, click <a href="https://arxiv.org/abs/2207.00026" target='_blank'>here</a> to check it out. Code will be available soon!

Installation

Please refer to INSTALL.md for the installation details.

Data Preparation

Please refer to DATA_PREPARE.md for the details to prepare the 1nuScenes, 2SemanticKITTI, and 3ScribbleKITTI datasets.

Getting Started

Please refer to GET_STARTED.md to learn more usage about this codebase.

Video Demo

Main Result

Framework Overview

Range View

<table> <tr> <th rowspan="2">Method</th> <th colspan="4">nuScenes</th> <th colspan="4">SemanticKITTI</th> <th colspan="4">ScribbleKITTI</th> </tr> <tr> <td>1%</td> <td>10%</td> <td>20%</td> <td>50%</td> <td>1%</td> <td>10%</td> <td>20%</td> <td>50%</td> <td>1%</td> <td>10%</td> <td>20%</td> <td>50%</td> </tr> <tr> <td>Sup.-only</td> <td>38.3</td> <td>57.5</td> <td>62.7</td> <td>67.6</td> <td>36.2</td> <td>52.2</td> <td>55.9</td> <td>57.2</td> <td>33.1</td> <td>47.7</td> <td>49.9</td> <td>52.5</td> </tr> <tr> <td>LaserMix</td> <td>49.5</td><td>68.2</td><td>70.6</td><td>73.0</td> <td>43.4</td><td>58.8</td><td>59.4</td><td>61.4</td> <td>38.3</td><td>54.4</td><td>55.6</td><td>58.7</td> </tr> <tr> <td>improv. &#8593</td> <td>+11.2</td> <td>+10.7</td> <td>+7.9</td> <td>+5.4</td> <td>+7.2</td> <td>+6.6</td> <td>+3.5</td> <td>+4.2</td> <td>+5.2</td> <td>+6.7</td> <td>+5.7</td> <td>+6.2</td> </tr> <tr> <td>LaserMix++</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>improv. &#8593</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> </table>

LaserMix

Install / Use

README