2026 | |
| Yang, T., Zou, Y., Del Rey Castillo, E., Hou, L. & Zhong, J. (2026): Enhancing Scan-to-BIM for reinforced concrete bridges using point cloud completion techniques. Automation in Construction, 181, 106606. DOI: 10.1016/j.autcon.2025.106606 | |
2025 | |
| Hanousek, T., Novotný, J., Navrátilová, B., Švik, M., Krejza, J. & Janoutová, R. (2025): Complete workflow for detailed 3D forest reconstruction: From terrestrial laser scanning to complex 3D radiative transfer modelling. In Silico Plants, 7(2), diaf019. DOI: 10.1093/insilicoplants/diaf019 | |
| She, Y., Blake, A., Coomes, D. & Keshav, S. (2025): Scaling Up Forest Vision with Synthetic Data. arXiv. DOI: 10.48550/ARXIV.2509.11201 | |
| Ali, M., Lohani, B., Hollaus, M. & Pfeifer, N. (2025): A hybrid approach for enhanced tree volume estimation of complex trees using terrestrial LiDAR. GIScience & Remote Sensing, 62(1). DOI: 10.1080/15481603.2025.2474836. | |
| Xia, J., Ma, S., Luan, G., Dong, P., Geng, R., Zou, F., Yin, J. & Zhao, Z. (2025): An Improved Method for Single Tree Trunk Extraction Based on LiDAR Data. Remote Sensing, 17(7), 1271. DOI: 10.3390/rs17071271 | |
| López, A., Ogayar, C., Segura, R. J. & Casas-Rosa, J. C. (2025): Enhancing LiDAR point cloud generation with BRDF-based appearance modelling. ISPRS Journal of Photogrammetry and Remote Sensing 222, pp. 79-98. DOI: 10.1016/j.isprsjprs.2025.02.010. | |
2024 | |
| Chen, Z., Shi, Y., Nan, L., Xiong, Z. & Zhu, X. (2023): PolyGNN: Polyhedron-based Graph Neural Network for 3D Building Reconstruction from Point Clouds. ISPRS Journal of Photogrammetry and Remote Sensing 218 (A), 693-706. DOI: 10.1016/j.isprsjprs.2024.09.031. | |
| Bornand, A., Abegg, M., Morsdorf, F., & Rehush, N. (2024): Completing 3D point clouds of individual trees using deep learning. Methods in Ecology and Evolution, 15 (11), 1–14. DOI: 10.1111/2041-210X.14412. | |
| Pečur, T., Bosché, F., Cerniauskas, G., Mill, F., Sherlock, A. & Yu, N. (2024): Prototype pipeline modelling using interval scanning point clouds. Advances in Manufacturing. DOI: 10.1007/s40436-024-00515-y. | |
| Yang, T., Zou, Y., Yang, X. & del Rey Castillo, E. (2024): Domain knowledge-enhanced region growing framework for semantic segmentation of bridge point clouds. Automation in Construction 165, 105572. DOI: 10.1016/j.autcon.2024.105572. | |
| Tang, S., Ao, Z., Li, Y., Huang, H., Xie, L., Wang, R., Wang, W. & Guo, R. (2024): TreeNet3D : A large scale tree benchmark for 3D tree modeling, carbon storage estimation and tree segmentation. International Journal of Applied Earth Observation and Geoinformation 130, 103903. DOI: 10.1016/j.jag.2024.103903. | |
| Cai, S., Zhang, W., Zhang, S., Yu, S. & Liang, X. (2024): Branch architecture quantification of large-scale coniferous forest plots using UAV-LiDAR data. Remote Sensing of Environment 306 (1), 114121. DOI: 10.1016/j.rse.2024.114121. | |
| Comesaña-Cebral L., Martínez-Sánchez J., Seoane A.N. & Arias P. (2024): Transport Infrastructure Management Based on LiDAR Synthetic Data: A Deep Learning Approach with a ROADSENSE Simulator. Infrastructures 9 (3), 58. DOI: 10.3390/infrastructures9030058. | |
| Noichl, F., Collins, F. C., Braun, A. & Borrmann, A. (2024): Enhancing point cloud semantic segmentation in the data-scarce domain of industrial plants through synthetic data. Computer-Aided Civil and Infrastructure Engineering, 1–20. DOI: 10.1111/mice.13153. | |
| Collins, F.C., Braun, A. & Borrmann, A. (2024): Finding Geometric and Topological Similarities in Building Elements for Large-Scale Pose Updates in Scan-vs-BIM. In: Skatulla, S. & Beushausen, H. (eds): Advances in Information Technology in Civil and Building Engineering. ICCCBE 2022. Lecture Notes in Civil Engineering, Vol. 357, Springer, Cham. DOI: 10.1007/978-3-031-35399-4_37. | |
2023 | |
| Lytkin, S., Badenko, V., Fedotov, A., Vinogradov, K., Chervak, A., Milanov, Y. & Zotov, D. (2023): Saint Petersburg 3D: Creating a Large-Scale Hybrid Mobile LiDAR Point Cloud Dataset for Geospatial Applications. Remote Sensing 15 (11), 2735. DOI: 10.3390/rs15112735. | |
| Stocker, O., Kouhi, R. M., Guilbert, E., Ferraz, A., Badard, T. (2023): Investigating the Impact of Point Cloud Density on Semantic Segmentation Performance Using Virtual Lidar in Boreal Forest. 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, pp. 978-981, DOI: 10.1109/IGARSS52108.2023.10282100. | |
2022 | |
| Eickeler, F. & Borrmann, A. (2022): Enhancing Railway Detection by Priming Neural Networks with Project Exaptations. Remote Sensing 14 (21), 5482. DOI: 10.3390/rs14215482. | |
| Kosse S., Vogt O., Wolf M., König M. & Gerhard D. (2022): Digital Twin Framework for Enabling Serial Construction. Frontiers in Built Environment 8. DOI: 10.3389/fbuil.2022.864722. | |
| Liu, X., Ma, Q., Wu, X., Hu, T., Liu, Z., Liu, L., Guo, Q. & Su, Y. (2022): A novel entropy-based method to quantify forest canopy structural complexity from multiplatform lidar point clouds. Remote Sensing of Environment 282. DOI: 10.1016/j.rse.2022.113280. | |
| Richter, K. & Maas, H.-G. (2022): Radiometric enhancement of full-waveform airborne laser scanner data for volumetric representation in environmental applications. ISPRS Journal of Photogrammetry and Remote Sensing. DOI: 10.1016/j.isprsjprs.2021.10.021. | |
| Saeed Mafipour, M., Alici, C., Saadat Shakeel, S., Kalkavan, A. (2022): Semantic Segmentation of Real and Synthetic Point Cloud Data for Digital Twinning of Bridges. Proceedings of 33. Forum Bauinformatik, 7–9 September 2022, pp. 378-386. DOI: 10.14459/2022md1686600. | |
| Wang, D., Puttonen, E. & Casella, E. (2022): PlantMove: A tool for quantifying motion fields of plant movements from point cloud time series. International Journal of Applied Earth Observation and Geoinformation 110. DOI: 10.1016/j.jag.2022.102781. | |
2021 | |
| Lecigne, B., Delagrange, S. & Taugourdeau, O. (2021): Annual Shoot Segmentation and Physiological Age Classification from TLS Data in Trees with Acrotonic Growth. Forests 12 (4). DOI: 10.3390/f12040391. | |
| Noichel, F., Braun, A. & Borrmann, A. (2021): BIM-to-Scan for Scan-to-BIM: Generating Realistic Synthetic Ground Truth Point Clouds based on Industrial 3D Models. 2021 European Conference on Computing in Construction, 27-28 July 2021, pp. 1-9. DOI: 10.35490/EC3.2021.166. | |
| Reitmann, S., Neumann, L. & Jung, B. (2021): BLAINDER - A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data. Sensors 21 (6). DOI: 10.3390/s21062144. | |
| Wu, B., Zheng, G., Chen, Y., Yu, D. (2021): Assessing inclination angles of tree branches from terrestrial laser scan data using a skeleton extraction method. International Journal of Applied Earth Observation and Geoinformation 104. DOI: 10.1016/j.jag.2021.102589. | |
2020 | |
| Li, L., Mu, X., Soma, M., Wan,P., Qi, J., Hu, R., Zhang, W., Tong, Y. & Yan, G. (2020): An Iterative-Mode Scan Design of Terrestrial Laser Scanning in Forests for Minimizing Occlusion Effects. IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2020.3018643. | |
| Park, M., Baek, Y., Dinare, M., Lee, D., Park, K.-H., Ahn, J., Kim, D., Medina, J., Choi, W.-J., Kim, S., Zhou, C., Heo, J. & Lee, K. (2020): Hetero-integration enables fast switching time-of-flight sensors for light detection and ranging. Sci Rep 10, 2764 (2020), pp. 1-8. DOI: 10.1038/s41598-020-59677-x. | |
| Schlager, B., Muckenhuber, S., Schmidt, S., Holzer, H. et al. (2020): State-of-the-Art Sensor Models for Virtual Testing of Advanced Driver Assistance Systems/Autonomous Driving Functions. SAE International Journal of Connected and Automated Vehicles 3 (3), pp. 233-261. DOI: 10.4271/12-03-03-0018. | |
| Wang, D. (2020): Unsupervised semantic and instance segmentation of forest point clouds. ISPRS Journal of Photogrammetry and Remote Sensing 165 (2020), pp. 86-97. DOI: 10.1016/j.isprsjprs.2020.04.020. | |
| Wang, D., Schraik, D., Hovi, A., Rautiainen, M.(2020): Direct estimation of photon recollision probability using terrestrial laser scanning. Remote Sensing of Environment 247 (2020), pp. 1-12. DOI: 10.1016/j.rse.2020.111932. | |
| Zhu, X., Liu, J., Skidmore, A.K., Premier, J., & Heurich, M. (2020): A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data. Remote Sensing of Environment, 240. DOI: 10.1016/j.rse.2020.111696. | |
2019 | |
| Lin, C.-H. & Wang, C.-K. (2019): Point Density Simulation for ALS Survey. Proceedings of the 11th International Conference on Mobile Mapping Technology (MMT2019), Shenzhen, China. pp. 157-160. | |
| Liu, J., Skidmore, A.K., Wang, T., Zhu, X., Premier, J., Heurich, M., Beudert, B. & Jones, S. (2019): Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest. ISPRS Journal of Photogrammetry and Remote Sensing, 148, pp. 208-220. DOI: 10.1016/j.isprsjprs.2019.01.005. | |
| Liu, J., Wang, T., Skidmore, A.K., Jones, S., Heurich, M., Beudert, B. & Premier, J. (2019): Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests. ISPRS Journal of Photogrammetry and Remote Sensing, 158, pp. 76-89. DOI: 10.1016/j.isprsjprs.2019.09.015. | |
| Martínez Sánchez, J., Álvarez, Á., Vilariño, D., Rivera, F., Cabaleiro, J. & Pena, T. (2019): Fast Ground Filtering of Airborne LiDAR Data Based on Iterative Scan-Line Spline Interpolation. Remote Sensing 11, pp. 1-23. DOI: 10.3390/rs11192256. | |
| Previtali, M., Díaz-Vilariño, L., Scaioni, M. & Frías Nores, E. (2019): Evaluation of the Expected Data Quality in Laser Scanning Surveying of Archaeological Sites. 4th International Conference on Metrology for Archaeology and Cultural Heritage, Florence, Italy, 4-6 December 2019, pp. 19-24. | |
| Xiao, W., Zaforemska, A., Smigaj, M., Wang, Y., Gaulton, R. (2019): Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data. Remote Sensing, 11, pp. 1-19. DOI: 10.3390/rs11111263. | |
| Zhang, Z., Li, J., Guo, Y. & Yang, C. (2019): 3D Highway Curve Reconstruction From Mobile Laser Scanning Point Clouds. IEEE Transactions on Intelligent Transportation Systems, pp. 1-11. DOI: 10.1109/TITS.2019.2946259. | |
2017 | |
| Rebolj, D., Pučko, Z., Babič, N.Č., Bizjak, M. & Mongus, D. (2017). Point cloud quality requirements for Scan-vs-BIM based automated construction progress monitoring. Automation in Construction, 84, pp. 323-334. DOI: 10.1016/j.autcon.2017.09.021. | |
