{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T21:49:07Z","timestamp":1775425747683,"version":"3.50.1"},"reference-count":132,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"DEVCOM Army Research Laboratory"},{"name":"US Army Simulation and Training Technology Center (STTC)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The recent surge in diverse 3D datasets spanning various scales and applications marks a significant advancement in the field. However, the comprehensive process of data acquisition, refinement, and annotation at a large scale poses a formidable challenge, particularly for individual researchers and small teams. To this end, we present a novel synthetic 3D point cloud generation framework that can produce detailed outdoor aerial photogrammetric 3D datasets with accurate ground truth annotations without the labor-intensive and time-consuming data collection\/annotation processes. Our pipeline procedurally generates synthetic environments, mirroring real-world data collection and 3D reconstruction processes. A key feature of our framework is its ability to replicate consistent quality, noise patterns, and diversity similar to real-world datasets. This is achieved by adopting UAV flight patterns that resemble those used in real-world data collection processes (e.g., the cross-hatch flight pattern) across various synthetic terrains that are procedurally generated, thereby ensuring data consistency akin to real-world scenarios. Moreover, the generated datasets are enriched with precise semantic and instance annotations, eliminating the need for manual labeling. Our approach has led to the development and release of the Semantic Terrain Points Labeling\u2014Synthetic 3D (STPLS3D) benchmark, an extensive outdoor 3D dataset encompassing over 16 km2, featuring up to 19 semantic labels. We also collected, reconstructed, and annotated four real-world datasets for validation purposes. Extensive experiments on these datasets demonstrate our synthetic datasets\u2019 effectiveness, superior quality, and their value as a benchmark dataset for further point cloud research.<\/jats:p>","DOI":"10.3390\/rs16224240","type":"journal-article","created":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T08:06:32Z","timestamp":1731571592000},"page":"4240","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["An Aerial Photogrammetry Benchmark Dataset for Point Cloud Segmentation and Style Translation"],"prefix":"10.3390","volume":"16","author":[{"given":"Meida","family":"Chen","sequence":"first","affiliation":[{"name":"Institute for Creative Technologies, University of Southern California, Los Angeles, CA 90094, USA"}]},{"given":"Kangle","family":"Han","sequence":"additional","affiliation":[{"name":"Astani Department of Civil and Environmental Engineering, USC Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90007, USA"}]},{"given":"Zifan","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Arizona State University, Tempe, AZ 85281, USA"}]},{"given":"Andrew","family":"Feng","sequence":"additional","affiliation":[{"name":"Institute for Creative Technologies, University of Southern California, Los Angeles, CA 90094, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9822-244X","authenticated-orcid":false,"given":"Yu","family":"Hou","sequence":"additional","affiliation":[{"name":"The Department of Construction Management, Western New England University, Springfield, MA 01119, USA"}]},{"given":"Suya","family":"You","sequence":"additional","affiliation":[{"name":"DEVCOM Army Research Laboratory, Los Angeles, CA 90089, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8701-0521","authenticated-orcid":false,"given":"Lucio","family":"Soibelman","sequence":"additional","affiliation":[{"name":"Astani Department of Civil and Environmental Engineering, USC Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90007, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Lin, Y.-C., Cheng, Y.-T., Zhou, T., Ravi, R., Hasheminasab, S.M., Flatt, J.E., Troy, C., and Habib, A. 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