A Dynamic Points Removal Benchmark in Point Cloud Maps

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 4530

05: KITTI sequence 05 [VLP-64] from frame 2350 to 2670

av2: Argoverse 2.0 one sequence on 07YOTznatmYypvQYpzviEcU3yGPsyaGg__Spring_2020. [2 x VLP-32]

semindoor: semi-indoor dataset collected by [VLP-16], collected by ourselves.

Dataset
Description
Sensor Type
Total Frame Number

KITTI sequence 00
in a small town with few dynamics (including one pedestrian around
VLP-64
141

KITTI sequence 05
in a small town straight way, one higher car, the benchmarking paper cover image from this sequeue
VLP-64
321

Argoverse2
in a big city, crowded and tall buildings (including cyclists, vehicles, people walking near the building etc.
2 x VLP-32
575

Semi-indoor
Collected by us, running on small 1x2 vehicle with two people walking around the platform
VLP-16
960

Cite 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}}