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Junjue-Wang

LoveDA

[NeurIPS 2021] LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

Model DevelopmentDataset engineeringPython
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创建于 2021-10-13 · 更新于 2026-10-16 · 今日第 6688 名
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Junjue-Wang/LoveDA 排名第 6,688,有 580 个星标。

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Junjue-Wang/LoveDA 排名第 6,688,此处有 8 个同类条目;ViktorAxelsen/MemSkill 排名第 6,678。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别Model Development
子类别Dataset engineering
关键词Computer vision, Datasets
星标数580
分叉数67
贡献者2
创建日期2021-10-13
更新日期2026-10-16
1 天星标数1
7 天星标数4
排名6,688
上次排名16,444
排名变化9,756
7 天星标排名6,470
上次 7 天星标排名5,794
7 天星标排名变化-676
总星标排名17,233
上次总星标排名17,229
总星标排名变化-4
国家Japan
README 摘录

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang , Zhuo Zheng , Ailong Ma, Xiaoyan Lu, and Yanfei Zhong [ ], [ ], [ ], [ ], [ ], [ ] News 2026/01/22, We moved the evaluation platform to LoveDA Semantic Segmentation Challenge , LoveDA Unsupervised Domain Adaptation Challenge . 2026/01/08, We extended the scope of LoveDA from China to a global scale at EarthVL dataset. 2024/05/12, The new version of LoveDA dataset has been released at EarthVQA dataset. 2021/12/13, Pre

-trained urls for HRNet have been updated. 2021/12/10, LoveDA has been included in Torchgeo . 2021/11/30, The contests have been moved to new server: LoveDA Semantic Segmentation Challenge , LoveDA Unsupervised Domain Adaptation Challenge . 2021/11/11, LoveDA has been included in MMsegmentation. 🔥🔥 The Semantic Segmentation task can be prepared follow dataset_prepare. 3 m) remote sensing images from Nanjing, Changzhou, and Wuhan 2. Focus on different geographical environments between Urban and Rural 3. Advance both semantic segmentation

and domain adaptation tasks 4. Three considerable challenges: Citation If you use LoveDA in your research, please cite our NeurIPS2021 paper. Dataset and Contest The LoveDA dataset is released at Zenodo and Baidu Drive Code: 27vc You can develop your models on Train and Validation sets. Category labels: background – 1, building – 2, road – 3, Submit your test results on LoveDA Semantic Segmentation Challenge , LoveDA Unsupervised Domain Adaptation Challenge . Feel free to design your own models, and we are looking forward

to your exciting results! License The owners of the data and of the copyright on the data are RSIDEA, Wuhan University. Use of the Google Earth images must respect the "Google Earth" terms of use. All images and their associated annotations in LoveDA can be used for academic purposes only, but any commercial use is prohibited.

常见问题

记录了多少星标和分叉?

Junjue-Wang/LoveDA 有 580 个星标和 67 个分叉。

仓库排名是多少?

Junjue-Wang/LoveDA 排名第 6,688。

记录的语言和类别是什么?

Junjue-Wang/LoveDA 有 580 个星标,语言为 Python,类别为 Model Development。

哪个仓库排名最接近?

Junjue-Wang/LoveDA 与 ViktorAxelsen/MemSkill 比较,后者排名第 6,678,有 582 个星标。

README

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zhong

[Paper], [Video], [Dataset], [BibTeX], [Leaderboard-SEG], [Leaderboard-UDA]

News

Highlights

  1. 5987 high spatial resolution (0.3 m) remote sensing images from Nanjing, Changzhou, and Wuhan
  2. Focus on different geographical environments between Urban and Rural
  3. Advance both semantic segmentation and domain adaptation tasks
  4. Three considerable challenges:
    • Multi-scale objects
    • Complex background samples
    • Inconsistent class distributions

Citation

If you use LoveDA in your research, please cite our NeurIPS2021 paper.

    @inproceedings{NEURIPS DATASETS AND BENCHMARKS2021_4e732ced,
         author = {Wang, Junjue and Zheng, Zhuo and Ma, Ailong and Lu, Xiaoyan and Zhong, Yanfei},
         booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},
         editor = {J. Vanschoren and S. Yeung},
         pages = {},
         publisher = {Curran Associates, Inc.},
         title = {LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation},
         url = {https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/file/4e732ced3463d06de0ca9a15b6153677-Paper-round2.pdf},
         volume = {1},
         year = {2021}
    }
    @dataset{junjue_wang_2021_5706578,
        author={Junjue Wang and Zhuo Zheng and Ailong Ma and Xiaoyan Lu and Yanfei Zhong},
        title={Love{DA}: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation},
        month=oct,
        year=2021,
        publisher={Zenodo},
        doi={10.5281/zenodo.5706578},
        url={https://doi.org/10.5281/zenodo.5706578}
    }

Dataset and Contest

The LoveDA dataset is released at Zenodo and Baidu Drive Code: 27vc

You can develop your models on Train and Validation sets.

Category labels: background – 1, building – 2, road – 3, water – 4, barren – 5,forest – 6, agriculture – 7. And the no-data regions were assigned 0 which should be ignored. The provided data loader will help you construct your pipeline.

Submit your test results on LoveDA Semantic Segmentation Challenge, LoveDA Unsupervised Domain Adaptation Challenge. You will get your Test scores smoothly.

Feel free to design your own models, and we are looking forward to your exciting results!

License

The owners of the data and of the copyright on the data are RSIDEA, Wuhan University. Use of the Google Earth images must respect the "Google Earth" terms of use. All images and their associated annotations in LoveDA can be used for academic purposes only, but any commercial use is prohibited.

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