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https://github.com/ZhangXiwuu/Awesome_visual_place_recognition_datasets
A curated list of Visual Place Recognition (VPR)/ loop closure detection (LCD) datasets
https://github.com/ZhangXiwuu/Awesome_visual_place_recognition_datasets
List: Awesome_visual_place_recognition_datasets
loop-closure loop-closure-detection place-recognition slam visual-place-recognition visual-slam
Last synced: about 1 month ago
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A curated list of Visual Place Recognition (VPR)/ loop closure detection (LCD) datasets
- Host: GitHub
- URL: https://github.com/ZhangXiwuu/Awesome_visual_place_recognition_datasets
- Owner: ZhangXiwuu
- Created: 2020-12-09T09:18:59.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2020-12-09T13:32:19.000Z (over 3 years ago)
- Last Synced: 2023-02-23T17:16:18.859Z (over 1 year ago)
- Topics: loop-closure, loop-closure-detection, place-recognition, slam, visual-place-recognition, visual-slam
- Homepage:
- Size: 17.6 KB
- Stars: 46
- Watchers: 4
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Lists
- awesome-object-detection-datasets - ZhangXiwuu/Awesome_visual_place_recognition_datasets
- ultimate-awesome - Awesome_visual_place_recognition_datasets - A curated list of Visual Place Recognition (VPR)/ loop closure detection (LCD) datasets. (Other Lists / Julia Lists)
README
# Awesome visual place recognition (VPR) datasets
This repository provides a curated list of awesome datasets for **Visual Place Recognition (VPR)**, which is also called **loop closure detection (LCD)**. It is a significant component in V-SLAM (Visual Simultaneous Localization and Mapping) systems.
**We will update the list if new VPR dataset is presented.**
Our survey paper on deep learning-based visual place recognition contains detailed information about these datasets:
> Xiwu Zhang, Lei Wang, and Yan Su. **Visual Place Recognition: A Survey From Deep Learning Perspective**. [_Pattern Recognition_](https://www.sciencedirect.com/journal/pattern-recognition), November 2020, doi: https://doi.org/10.1016/j.patcog.2020.107760.
## Datasets used in VPR.
This list summarizes public available datasets that can be used for visual place recognition. We devide them into multiple categories according to different research topics, for example, long-term, across-seasons, semantic VPR and so on.
| Topic | Name | Year | Image type | Environment | Illumination | Viewpoint | Ground Truth | Labels | Extra Information |
| ----------------- | ------------------------------------------------------------ | ---- | --------------- | --------------- | ------------------ | ------------------ | ------------------ | ------------------ | ----------------- |
| Generic | [New College and City Centre](http://www.robots.ox.ac.uk/~mobile/IJRR_2008_Dataset/data.html) [1] | 2008 | RGB | Outdoor | slight | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | GPS |
| | [New College Vision and Laser ](https://ori.ox.ac.uk/older-projects/new-college-dataset/) [2] | 2009 | Gray\. | Outdoor | slight | :heavy_check_mark: | :heavy_check_mark: | | GPS, IMU, LiDAR |
| | [Rawseeds](http://www.rawseeds.org/home/) | 2006 | RGB | Indoor/Outdoor | | :heavy_check_mark: | :heavy_check_mark: | | GPS, LiDAR |
| | [Ford Campus](http://robots.engin.umich.edu/SoftwareData/Ford) | 2011 | RGB | Urban | slight | | :heavy_check_mark: | | GPS, IMU, LiDAR |
| | [Malaga Parking 6L](https://www.mrpt.org/malaga_dataset_2009) | 2009 | RGB | Outdoor | | | :heavy_check_mark: | | GPS, IMU, LiDAR |
| | [KITTI Odometry](http://www.cvlibs.net/datasets/kitti/eval_odometry.php) | 2012 | Gray\./ RGB | Urban | slight | | :heavy_check_mark: | | GPS, IMU, LiDAR |
| Long\-term | [St\. Lucia](https://wiki.qut.edu.au/display/cyphy/St+Lucia+Multiple+Times+of+Day) | 2010 | RGB | Urban | :heavy_check_mark: | slight | | | GPS |
| | [COLD](https://www.nada.kth.se/cas/COLD/) | 2009 | RGB | Indoor | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | LiDAR |
| | [Oxford RobotCar](https://robotcar-dataset.robots.ox.ac.uk/) | 2017 | RGB | Urban | :heavy_check_mark: | | :heavy_check_mark: | | GPS, IMU, LiDAR |
| | [Gardens Point Walking](https://goo.gl/tqmWyq) | 2014 | RGB | Indoor/ Outdoor | :heavy_check_mark: | :heavy_check_mark: | | | \- |
| | [MSLS](https://www.mapillary.com/dataset/places) | 2020 | RGB | Urban | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | GPS |
| Across seasons | [Nurburgring and Alderley](https://wiki.qut.edu.au/display/cyphy/Michael+Milford+Datasets+and+Downloads) | 2012 | RGB | Urban | :heavy_check_mark: | | :heavy_check_mark: | :heavy_check_mark: | \- |
| | [Nordland](https://nrkbeta.no/2013/01/15/) | 2013 | RGB | Outdoor | :heavy_check_mark: | | :heavy_check_mark: | | GPS |
| | [CMU](http://3dvis.ri.cmu.edu/data-sets/localization/) | 2011 | RGB | Urban | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | GPS |
| | [Freiburg \(FAS\)](http://aisdatasets.informatik.uni-freiburg.de/freiburg_across_seasons/) | 2014 | RGB | Urban | :heavy_check_mark: | | :heavy_check_mark: | :heavy_check_mark: | GPS |
| | [VPRiCE](https://goo.gl/R0QYU2) | 2015 | RGB | Outdoor | :heavy_check_mark: | :heavy_check_mark: | | | \- |
| RGB\-D | [TUM RGB\-D](https://vision.in.tum.de/data/datasets/rgbd-dataset) | 2012 | RGB\-D | Indoor | | :heavy_check_mark: | :heavy_check_mark: | | IMU |
| | [Microsoft 7\-Scenes](https://www.microsoft.com/en-us/research/project/rgb-d-dataset-7-scenes/) | 2013 | RGB\-D | Indoor | | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | \- |
| | [ICL\-NUIM](https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html) | 2014 | RGB\-D | Indoor | | :heavy_check_mark: | :heavy_check_mark: | | \- |
| Semantic | [KITTI Semantic](http://www.cvlibs.net/datasets/kitti/eval_semantics.php) | 2019 | RGB | Urban | | | :heavy_check_mark: | :heavy_check_mark: | GPS, IMU, LiDAR |
| | [Cityscapes](https://www.cityscapes-dataset.com/) | 2016 | RGB | Urban | | | :heavy_check_mark: | :heavy_check_mark: | GPS |
| | [CSC](https://www.visuallocalization.net/datasets/) | 2019 | RGB | Outdoor | :heavy_check_mark: | | :heavy_check_mark: | | LiDAR |
| Train networks | [Cambridge Landmarks](http://mi.eng.cam.ac.uk/projects/relocalisation/#dataset) | 2015 | RGB | Outdoor | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | \- |
| | [Pittsburgh250k](http://www.ok.ctrl.titech.ac.jp/~torii/project/repttile/) | 2013 | RGB | Urban | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | GPS |
| | [Tokyo 24/7](http://www.ok.ctrl.titech.ac.jp/~torii/project/247/) | 2015 | RGB | Urban | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | GPS |
| | [SPED](https://goo.gl/OXeL2X) | 2017 | RGB | Outdoor | :heavy_check_mark: | :heavy_check_mark: | | | \- |
| Omni\-directional | [New College Vision and Laser](https://ori.ox.ac.uk/older-projects/new-college-dataset/) | 2009 | Gray\. | Outdoor | slight | :heavy_check_mark: | :heavy_check_mark: | | GPS, IMU, LiDAR |
| | [MOLP](http://hcr.mines.edu/code/MOLP.html) | 2018 | Gray\./D | Outdoor | :heavy_check_mark: | | :heavy_check_mark: | | GPS |
| | [NCLT](http://robots.engin.umich.edu/nclt/) | 2016 | RGB | Outdoor | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | GPS, LiDAR |
| Aerial/UAV | [Shopping Street 1/2](http://www.v4rl.ethz.ch/research/datasets-code.htmls) | 2018 | Gray\. | Urban | slight | :heavy_check_mark: | :heavy_check_mark: | | \- |
| | [EuRoC](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdataset) | 2016 | Gray\. | Indoor | | :heavy_check_mark: | :heavy_check_mark: | | IMU |
| Underwater | [UWSim](https://goo.gl/GtMQkv) | 2016 | RGB | Under\-water | | | :heavy_check_mark: | | GPS |
| Range sensors | [MulRan](https://sites.google.com/view/mulran-pr) | 2020 | 3D Point clouds | Urban | :heavy_check_mark: | | :heavy_check_mark: | | LiDAR, RADAR |
## Reference:
[1] Cummins, M. & Newman, P. __FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance.__ The International Journal of Robotics Research, 2008, 27, 647-665
[2] M. Smith, I. Baldwin, W. Churchill, R. Paul, P. Newman, The new college vi- sion and laser data set, Int. J. Rob. Res. 28 (5) (2009) 595–599, doi: 10.1177/ 0278364909103911 .
- [ ] TODO ...
---
Citations to this work:
```
@article{ZHANG2020107760,
title = "Visual place recognition: A survey from deep learning perspective",
journal = "Pattern Recognition",
pages = "107760",
year = "2020",
issn = "0031-3203",
doi = "https://doi.org/10.1016/j.patcog.2020.107760",
url = "http://www.sciencedirect.com/science/article/pii/S003132032030563X",
author = "Xiwu Zhang and Lei Wang and Yan Su",
}
```