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@@ -40,8 +40,8 @@ Here is a preview of the readme in codes. Task detects dynamic points in maps an
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Feel free to pull a request if you want to add more methods or datasets. Welcome! We will try our best to update methods and datasets in this benchmark. Please give us a star 🌟 and cite our work 📖 if you find this useful for your research. Thanks!
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-**2024/04/29**[BeautyMap](https://arxiv.org/abs/2405.07283) is accepted by RA-L'24. Updated benchmark: BeautyMap and DeFlow submodule instruction in the benchmark. Added the first data-driven method [DeFlow](https://github.com/KTH-RPL/DeFlow/tree/feature/dynamicmap) into our benchmark. Feel free to check.
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-**2024/04/18**[DUFOMap](https://arxiv.org/abs/2403.01449) is accepted by RA-L'24. Updated benchmark: DUFOMap and dynablox submodule instruction in the benchmark. Two datasets w/o gt for demo are added in the download link. Feel free to check.
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-**2024/03/18** Added the first data-driven method [DeFlow](https://github.com/KTH-RPL/DeFlow/tree/feature/dynamicmap) into our benchmark. Create [BeautyMap](https://github.com/HKUSTGZ-IADC/BeautyMap) repo (wait for public and open-source after review).
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-**2024/03/08****Fix statements** on our ITSC'23 paper: KITTI sequences pose are also from SemanticKITTI which used SuMa. In the DUFOMap paper Section V-C, Table III, we present the dynamic removal result on different pose sources. Check discussion in [DUFOMap](https://arxiv.org/abs/2403.01449) paper if you are interested.
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-**2023/06/13** The [benchmark paper](https://arxiv.org/abs/2307.07260) Accepted by ITSC 2023 and release five methods (Octomap, Octomap w GF, ERASOR, Removert) and three datasets (01, 05, av2, semindoor) in [benchmark paper](https://arxiv.org/abs/2307.07260).
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@@ -64,7 +64,7 @@ Learning-based (data-driven) (w pretrain-weights provided):
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