docs(data): upload new datasets: twofloor and kthcampus. Check it out!

Author: Kin-Zhang

README.md

@@ -40,14 +40,14 @@ Here is a preview of the readme in codes. Task detects dynamic points in maps an
 
 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!
 
-- **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. Datasets will soon be updated.
+- **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.
 - **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).
 - **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.
 - **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).
 
 ---
 
-- [ ] 2024/03/27: I will update a document page soon (tutorial, manual book, and new online leaderboard), and point out the commit for each paper. Since there are some minor mistakes in the first version. Stay tune with us!
+- [ ] 2024/04/19: I will update a document page soon (tutorial, manual book, and new online leaderboard), and point out the commit for each paper. Since there are some minor mistakes in the first version. Stay tune with us!
 
 
 ## Methods:
@@ -77,14 +77,14 @@ Last but not least, feel free to pull request if you want to add more methods. W
 
 ## Dataset & Scripts
 
-Download all these dataset from [Zenodo online drive](https://zenodo.org/record/8160051). Or create by yourself through the [scripts we provided](scripts/README.md).
+Download all these dataset from [Zenodo online drive](https://zenodo.org/records/10886629). Or create by yourself through the [scripts we provided](scripts/README.md).
 
 - [x] [Semantic-Kitti, outdoor small town](https://semantic-kitti.org/dataset.html) VLP-64
 - [x] [Argoverse2.0, outdoor US cities](https://www.argoverse.org/av2.html#lidar-link) VLP-32
 - [x] [UDI-Plane] Our own dataset, Collected by VLP-16 in a small vehicle.
-- [ ] [KTH-Campuse] Our [Multi-Campus Dataset](https://mcdviral.github.io/), Collected by [Leica RTC360 3D Laser Scan](https://leica-geosystems.com/products/laser-scanners/scanners/leica-rtc360).
-- [ ] [HKUST-Building] Our [fusionportable Dataset](https://fusionportable.github.io/dataset/fusionportable/), collected by [Leica BLK360 Imaging Laser Scanner](https://leica-geosystems.com/products/laser-scanners/scanners/blk360)
-- [ ] [Indoor-Floor] Our own dataset, Collected by Livox mid-360 in a quadruped robot.
+- [x] [KTH-Campuse] Our [Multi-Campus Dataset](https://mcdviral.github.io/), Collected by [Leica RTC360 3D Laser Scan](https://leica-geosystems.com/products/laser-scanners/scanners/leica-rtc360). Only 18 frames included to download for demo, please check [the official website](https://mcdviral.github.io/) for more.
+- [x] [Indoor-Floor] Our own dataset, Collected by Livox mid-360 in a quadruped robot.
+<!-- - [ ] [HKUST-Building] Our [fusionportable Dataset](https://fusionportable.github.io/dataset/fusionportable/), collected by [Leica BLK360 Imaging Laser Scanner](https://leica-geosystems.com/products/laser-scanners/scanners/blk360) -->
 <!-- - [ ] [KTH-Indoor] Our own dataset, Collected by VLP-16/Mid-70 in kobuki. -->
 
 Welcome to contribute your dataset with ground truth to the community through pull request.
@@ -103,6 +103,8 @@ Check [create dataset readme part](scripts/README.md#evaluation) in the scripts
 
 This benchmark implementation is based on codes from several repositories as we mentioned in the beginning. Thanks for these authors who kindly open-sourcing their work to the community. Please see our paper reference section to get more information.
 
+Thanks to HKUST Ramlab's members: Bowen Yang, Lu Gan, Mingkai Tang, and Yingbing Chen, who help collect additional datasets.
+
 This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program ([WASP](https://wasp-sweden.org/)) funded by the Knut and Alice Wallenberg Foundation
 
 ### Cite Our Papers