Synthetic LiDAR sequential point cloud dataset with point-wise annotations

Related tags

Deep Learning SynLiDAR
Overview

arXiv

SynLiDAR dataset: Learning From Synthetic LiDAR Sequential Point Cloud

This is official repository of the SynLiDAR dataset. For technical details, please refer to:

SynLiDAR: Learning From Synthetic LiDAR Sequential Point Cloud for Semantic Segmentation (Paper)

Aoran Xiao, Jiaxing Huang, Dayan Guan, Fangneng Zhan, Shijian Lu

News

[2021.Jul.28] SynLiDAR is available for download!

Dataset

SynLiDAR is a large-scale synthetic LiDAR sequential point cloud dataset with point-wise annotations. 13 sequences of LiDAR point cloud with around 20k scans (over 19 billion points and 32 semantic classes) are collected from virtual urban cities, suburban towns, neighborhood, and harbor.

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Download (245.3GB)

  1. You can download SynLiDAR through browser → DR-NTU

  2. You can also download through provided python script, this requires installing pyDataverse

pip install pyDataverse
python download.py

Note: For most of sequences, we compressed and split them into multiple small files. Please download them and cat into one file before extraction. E.g. for sequence 01:

cat 01*>01.tar.gz
tar -zxvf 11.tar.gz

The data should organized in the following format:

/SynLiDAR/
  └── 00/
    └── velodyne
      └── 000000.bin
      ├── 000001.bin
      ...
    └── labels
      └── 000000.label
      ├── 000001.label
      ...
  ...
  └── annotations.yaml
  └── read_data.py

We provide class annotations (in 'annotations.yaml') and example python code for reading data (in 'read_data.py').

Citation

If you find our work useful in your research, please consider citing:

@article{xiao2021synlidar,  
  title={SynLiDAR: Learning From Synthetic LiDAR Sequential Point Cloud for Semantic Segmentation},  
  author={Xiao, Aoran and Huang, Jiaxing and Guan, Dayan and Zhan, Fangneng and Lu, Shijian},  
  journal={arXiv preprint arXiv:2107.05399},  
  year={2021}  
}
Comments
  • Download issue

    Download issue

    image Hello,

    Thanks for your awesome work. Now I am trying to download the dataset using the provided download.py. However, as shown in the above figure, the size of all downloaded subsets could not exceed 5.9 GB, so I want to if there is any constraint on the server or any other things I should check.

    Thanks

    opened by Solacex 7
  • LiDAR sensor specification

    LiDAR sensor specification

    Thank you very much for the interesting work and providing the dataset.

    I was wondering, which LiDAR sensor you simulated (if you had a specific selected) when generating the dataset or if you have the specifications (like angles, number of beams , number of points per beam) of the sensor that you simulate.

    Thank you very much again. Best,

    opened by BjoernMichele 2
  • About the dataset used in paper

    About the dataset used in paper

    Hi, Aoran Xiao. Thank you for your brilliant work.

    I see that "-- SubDataset: uniformlly downsampled dataset (about 24GB), this is the dataset that we used in Paper. You are recommend to use this smaller dataset for faster experiments." in readme file.

    To fairly compare with your method, I would like to confirm that all the experimental results in your paper "Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation" use SubDataset?

    opened by dream-toy 2
  • Affine transformation matrices

    Affine transformation matrices

    Hi!

    thanks for the dataset! Each sequence is provided in the sensor frame therefore it is impossible to accurately register all the frames. Are you going to provide calibration files with affine transform matrices for registering the frames?

    Thanks in advance!

    opened by saltoricristiano 2
  • Will could provide an google cloud /baidu cloud download?

    Will could provide an google cloud /baidu cloud download?

    Hello,

    Thanks for your awesome work. Will you consider releasing this dataset on google/Baidu cloud? We found it difficult to download such a large dataset from the current server.

    Thanks.

    opened by Solacex 2
  • Could you provide more information about intensity rendering model?

    Could you provide more information about intensity rendering model?

    I noticed on you paper that "Detailed descriptions about the rendering model and experiments are presented in Appendix" but I can't find the appendix nowhere. Could you kindly provide some more information about that? Thanks!

    opened by Beastmaster 1
  • Question about the class mapping

    Question about the class mapping

    Hi, Aoran Xiao. First of all, thank you very much for the previous sharing of the mapping file. But I have a question. Why is the mapping categories of SemanticPoss in the file inconsistent with the categories given in the paper?

    opened by kongxin123456 1
  • Question about the class mapping

    Question about the class mapping

    Hi, Aoran Xiao. Firstly, thank you for your brilliant work! I see that you have given an example of class mapping from synlidar to semantickitti. And could you share the YAML file of semanticPOSS with me too? Please help.

    opened by kongxin123456 1
  • Class mapping from index to name

    Class mapping from index to name

    Dear authors,

    thank you very much for your very interesting work. In my actual project I would need to name each class index but, unfortunately, I found it is missing a mapping between class indexes [0, 31] and class names [road, .., table]. Can you please provide the mapping between index-name?

    Thank you in advance!

    opened by saltoricristiano 1
  • Lidar Pose Missing

    Lidar Pose Missing

    Dear @xiaoaoran,

    I would like to start by expressing my appreciation for your work. It is interesting and inspires the research community for UDA tasks.

    I have downloaded the dataset and found out that the Pose (the transformation matrix between local to global coordinate systems) information regarding the Ego-vehicle/Lidar Sensor is missing. Can you please point me where it is stored?

    Thank you. Looking forward to hearing from you soon.

    opened by awethaileslassie 2
  • Source Code for PCT

    Source Code for PCT

    Thank you for the interesting work.

    Would you like to share the code for PCT? Especially, the code for the appearance translation module and the sparsity translation module. Thanks!

    opened by ldkong1205 6
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