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A multi-modal, photo-realistic dataset for online end-to-end scene change detection and more (accepted to IROS2021).

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ChangeSim

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This repository provides ChangeSim dataset, codes and files for evaluation. Please refer to our paper (accepted to IROS2021) for more information about the dataset.

Recent updates

  • Dataset download links
  • Documentation for the dataset
  • A tutorial for the visualization of ChangeSim
  • A tutorial for the data collection using Airsim and UE4

Dataset download

The data is divided into train/test set and reference/query.

Reference_Sequence_Train(52.8 GB)

Reference_Sequence_Test(30.2 GB)

Query_Sequence_Train(42.8 GB)

Query_Sequence_Test(30.3 GB)

Data directory structure

Ref_Seq_
|
--- Warehouse_0                              # Environment folder
|       |
|       ---- Seq_0                           # Sequece
|       |      |
|       |      +--- rgb                      # 0.png - xxxx.png      
|       |      +--- depth                    # 0.png - xxxx.png
|       |      +--- semantic_segmentation    # 0.png - xxxx.png     
|       |      ---- raw                   
|       |      |     |
|       |      |     +--- rgb                # 0.png - xxxx.png
|       |      |     +--- depth              # 0.png - xxxx.png
|       |      |     ---- poses.g2o 
|       |      |     ---- rtabmap.yaml
|       |
|       +--- Seq_1
|
+-- Warehouse_1
.
.
+-- Warehouse_N



Query_Seq_
|
--- Warehouse_0                              # Environment folder
|       |
|       ---- Seq_0                           # Sequece
|       |      |
|       |      +--- rgb                      # 0.png - xxxx.png      
|       |      +--- depth                    # 0.png - xxxx.png
|       |      +--- semantic_segmentation    # 0.png - xxxx.png
|       |      +--- change_segmentation      # 0.png - xxxx.png
|       |      +--- pose                     # 0.txt - xxxx.txt
|       |      ---- t0                   
|       |      |     |
|       |      |     +--- rgb                # 0.png - xxxx.png
|       |      |     +--- depth              # 0.png - xxxx.png
|       |      |     +--- idx                # 0.txt - xxxx.txt
|       |      ---- cloud_map.ply
|       |      ---- trajectory.txt
|       |
|       +--- Seq_0_dust
|       .
|       .
|       +--- Seq_1_dark
|
+-- Warehouse_1
.
.
+-- Warehouse_N

Citation

If you find this project helpful, please consider citing this project in your publications. The following is the BibTeX of our work.

@inproceedings{park2021changesim,
author = {Park, Jin-Man and Jang, Jae-hyuk, and Yoo, Sahng-Min and Lee, Sun-Kyung and Kim, Ue-hwan and Kim, Jong-Hwan},
title = {ChangeSim: Towards End-to-End Online Scene Change Detection in Industrial Indoor Environments},
booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
year = {2021},
organization = {IEEE},
url = {https://arxiv.org/abs/2103.05368},
}

Acknowledgement

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2020-0-00440, Development of artificial intelligence technology that continuously improves itself as the situation changes in the real world).

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A multi-modal, photo-realistic dataset for online end-to-end scene change detection and more (accepted to IROS2021).

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