Uniformat Dataset LiDAR Point Cloud Data [PCD format: with pose and points (x,y,z,/i)] We recommend you read this wiki page first to know about data: https://kth-rpl.github.io/DynamicMap_Benchmark/data/For methods detail: DynamicMap_Benchmark repo, DUFOMap, BeautyMap.00: KITTI sequence 00 [VLP-64] from frame 4390 to 453005: KITTI sequence 05 [VLP-64] from frame 2350 to 2670av2: Argoverse 2.0 one sequence on 07YOTznatmYypvQYpzviEcU3yGPsyaGg__Spring_2020. [2 x VLP-32]KTH campus: CVPR'24 MCD(Leica RTC360) For convenience teaser running, we include only 18 frames in data. Please check the MCD project page for more.semindoor: semi-indoor dataset collected by [VLP-16], collected by ourselves. twofloor: complex structure with two floors[Livox mid-360], collected by ourselves. DatasetDescriptionSensor TypeTotal Frame NumberKITTI sequence 00in a small town with few dynamics (including one pedestrian around)VLP-64141KITTI sequence 05in a small town straight way, one higher car, the benchmarking paper cover image from this sequence.VLP-64321Argoverse2in a big city, crowded and tall buildings (including cyclists, vehicles, people walking near the building etc.2 x VLP-32575KTH campus (no gt)Collected by us (Thien-Minh) on the KTH campus. Lots of people move around on the campus.  The DUFOMap paper cover image is from this one.Leica RTC36018Semi-indoorCollected by us (Qingwen & Mingkai), running on a small 1x2 vehicle with two people walking around the platform.VLP-16960Twofloor (no gt)Collected by us (Bowen Yang) in a quadruped robot. A two-floor structure environment with one pedestrian around.Livox-mid 3603305 Cite as:@inproceedings{zhang2023benchmark,  author={Zhang, Qingwen and Duberg, Daniel and Geng, Ruoyu and Jia, Mingkai and Wang, Lujia and Jensfelt, Patric},  booktitle={IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},   title={A Dynamic Points Removal Benchmark in Point Cloud Maps},   year={2023},  pages={608-614},  doi={10.1109/ITSC57777.2023.10422094}}@article{jia2024beautymap,  author={Jia, Mingkai and Zhang, Qingwen and Yang, Bowen and Wu, Jin and Liu, Ming and Jensfelt, Patric},  journal={IEEE Robotics and Automation Letters},   title={{BeautyMap}: Binary-Encoded Adaptable Ground Matrix for Dynamic Points Removal in Global Maps},   year={2024},  volume={9},  number={7},  pages={6256-6263},  doi={10.1109/LRA.2024.3402625}}@article{daniel2024dufomap,  author={Duberg, Daniel and Zhang, Qingwen and Jia, Mingkai and Jensfelt, Patric},  journal={IEEE Robotics and Automation Letters},   title={{DUFOMap}: Efficient Dynamic Awareness Mapping},   year={2024},  volume={9},  number={6},  pages={5038-5045},  doi={10.1109/LRA.2024.3387658}} If you use this data, feel free to add your project to https://kth-rpl.github.io/DynamicMap_Benchmark/papers/

Uniformat Dataset LiDAR Point Cloud Data [PCD format: with pose and points (x,y,z,/i)] We recommend you read this wiki page first to know about data: https://kth-rpl.github.io/DynamicMap_Benchmark/data/For methods detail: DynamicMap_Benchmark repo, DUFOMap, BeautyMap.00: KITTI sequence 00 [VLP-64] from frame 4390 to 453005: KITTI sequence 05 [VLP-64] from frame 2350 to 2670av2: Argoverse 2.0 one sequence on 07YOTznatmYypvQYpzviEcU3yGPsyaGg__Spring_2020. [2 x VLP-32]KTH campus: CVPR'24 MCD(Leica RTC360) For convenience teaser running, we include only 18 frames in data. Please check the MCD project page for more.semindoor: semi-indoor dataset collected by [VLP-16], collected by ourselves. twofloor: complex structure with two floors[Livox mid-360], collected by ourselves. DatasetDescriptionSensor TypeTotal Frame NumberKITTI sequence 00in a small town with few dynamics (including one pedestrian around)VLP-64141KITTI sequence 05in a small town straight way, one higher car, the benchmarking paper cover image from this sequence.VLP-64321Argoverse2in a big city, crowded and tall buildings (including cyclists, vehicles, people walking near the building etc.2 x VLP-32575KTH campus (no gt)Collected by us (Thien-Minh) on the KTH campus. Lots of people move around on the campus.  The DUFOMap paper cover image is from this one.Leica RTC36018Semi-indoorCollected by us (Qingwen & Mingkai), running on a small 1x2 vehicle with two people walking around the platform.VLP-16960Twofloor (no gt)Collected by us (Bowen Yang) in a quadruped robot. A two-floor structure environment with one pedestrian around.Livox-mid 3603305 Cite as:@inproceedings{zhang2023benchmark,  author={Zhang, Qingwen and Duberg, Daniel and Geng, Ruoyu and Jia, Mingkai and Wang, Lujia and Jensfelt, Patric},  booktitle={IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},   title={A Dynamic Points Removal Benchmark in Point Cloud Maps},   year={2023},  pages={608-614},  doi={10.1109/ITSC57777.2023.10422094}}@article{jia2024beautymap,  author={Jia, Mingkai and Zhang, Qingwen and Yang, Bowen and Wu, Jin and Liu, Ming and Jensfelt, Patric},  journal={IEEE Robotics and Automation Letters},   title={{BeautyMap}: Binary-Encoded Adaptable Ground Matrix for Dynamic Points Removal in Global Maps},   year={2024},  volume={9},  number={7},  pages={6256-6263},  doi={10.1109/LRA.2024.3402625}}@article{daniel2024dufomap,  author={Duberg, Daniel and Zhang, Qingwen and Jia, Mingkai and Jensfelt, Patric},  journal={IEEE Robotics and Automation Letters},   title={{DUFOMap}: Efficient Dynamic Awareness Mapping},   year={2024},  volume={9},  number={6},  pages={5038-5045},  doi={10.1109/LRA.2024.3387658}} If you use this data, feel free to add your project to https://kth-rpl.github.io/DynamicMap_Benchmark/papers/

Uniformat Dataset LiDAR Point Cloud Data [PCD format]check DynamicMap_Benchmark repo and Our Papers for more detail.00: KITTI sequence 00 [VLP-64] from frame 4390 to 453005: KITTI sequence 05 [VLP-64] from frame 2350 to 2670av2: Argoverse 2.0 one sequence on 07YOTznatmYypvQYpzviEcU3yGPsyaGg__Spring_2020. [2 x VLP-32]semindoor: semi-indoor dataset collected by [VLP-16], collected by ourselves. DatasetDescriptionSensor TypeTotal Frame NumberKITTI sequence 00in a small town with few dynamics (including one pedestrian aroundVLP-64141KITTI sequence 05in a small town straight way, one higher car, the benchmarking paper cover image from this sequeueVLP-64321Argoverse2in a big city, crowded and tall buildings (including cyclists, vehicles, people walking near the building etc.2 x VLP-32575Semi-indoorCollected by us, running on small 1x2 vehicle with two people walking around the platformVLP-16960Cite as:@inproceedings{zhang2023benchmark,  author={Zhang, Qingwen and Duberg, Daniel and Geng, Ruoyu and Jia, Mingkai and Wang, Lujia and Jensfelt, Patric},  booktitle={2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},   title={A Dynamic Points Removal Benchmark in Point Cloud Maps},  year={2023}, pages={608-614},  doi={10.1109/ITSC57777.2023.10422094}}