2026-05-08T06:16:59Z https://researchdata.tuwien.ac.at/oai2d

oai:researchdata.tuwien.ac.at:443tr-j4096 2025-09-26T09:36:56Z openaire_data

4.3 TUW.TUDATA 10.48436/443tr-j4096 oai:researchdata.tuwien.ac.at:443tr-j4096 Erler, Philipp Philipp Erler TU Wien Herzberger, Lukas Lukas Herzberger 0000-0002-9047-065X TU Wien Wimmer, Michael Michael Wimmer 0000-0002-9370-2663 TU Wien Schütz, Markus Markus Schütz 0000-0002-8166-3089 TU Wien TU Wien 2025 Aerial LIDAR surface reconstruction neural networks heightmap point cloud 2025-06 2025-09-26 eng 10.2312/hpg.20251170 10.48436/z57zg-n8m42 Creative Commons Attribution 4.0 International MIT License LidarScout: Direct Out-of-Core Rendering of Massive Point Clouds This dataset contains data related to our LidarScout paper at High-Performance Graphics 2025. This paper proposes a method for instantly exploring huge, compressed point clouds (LAZ) without any pre-processing and no extra storage. Contained data is: LidarScout executable for Windows (requires CUDA) A screen-capture video as MP4 Source code for the viewer (Github Snapshot from 2025-09-25, https://github.com/cg-tuwien/lidarscout, mostly C++ and CUDA) Source code for the training (Github Snapshot from 2025-09-25, https://github.com/cg-tuwien/lidarscout_training, mostly Python) Trained models for all variants as Pytorch checkpoints (.ckpt) and Torchscript (.pt) Training and testing datasets based on AHN5, Bund_BoraPk, CA13, ID15_Bunds, NZ23_Gisborne, BR17_SaoPaulo, and SwissSurface3D as CSV, PLY, and BIN files. Testing results for all model variants and all test datasets as PLY and NPY files More detailed information on the folder and file structure can be found in the README of the training repository. More general information: https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/ There are some scripts provided in the code archive for very interested users; they may require a little bit of tinkering to get them to run. Licenses The data is licensed under CC-BY 4.0, the code is licensed under MIT. Acknowledgements We thank the following data set providers: Bunds at el. and Open Topography for the Bund_Bora [ BDG+19] and ID15_Bunds [BDG+20] data sets; PG&E and Open Topography for CA13 [ Pac13 ]; The Ministry of Business, Innovation and Employment and Toit¯u Te Whenua Land Information New Zealand and Open Topography for Gisborne [ MoBE24 ]; The São Paulo City Hall (PMSP) and Open Topography for São Paulo [ (PM17 ]; The Bundesamt für Landestopografie swisstopo for swissSURFACE3D [Swi20]. We thank Paul Guerrero, Pedro Hermosilla, and Adam Celarek for their valuable inputs. Further, we thank Stefan Ohrhallinger for running reconstructions with BallMerge [POEM24].This research has been funded by WWTF project ICT22-055 - Instant Visualization and Interaction for Large Point Clouds. Vienna Science and Technology Fund 01f9mc681 ICT22-055 Instant Visualization and Interaction for Large Point Clouds