ISPRS BENCHMARK FOR MULTI-PLATFORM PHOTOGRAMMETRY

80 citations as recorded by crossref.

1. Deep learning feature representation for image matching under large viewpoint and viewing direction change L. Chen & C. Heipke https://doi.org/10.1016/j.isprsjprs.2022.06.003
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5. 3-D Line Segment Reconstruction With Depth Maps for Photogrammetric Mesh Refinement in Man-Made Environments T. Fang et al. https://doi.org/10.1109/TGRS.2023.3332211
6. A Two-Stage Deep Learning Registration Method for Remote Sensing Images Based on Sub-Image Matching Y. Chen & J. Jiang https://doi.org/10.3390/rs13173443
7. Automatic Rough Georeferencing of Multiview Oblique and Vertical Aerial Image Datasets of Urban Scenes S. Verykokou & C. Ioannidis https://doi.org/10.1111/phor.12156
8. Towards depth estimation in a single aerial image L. Pellegrin & J. Martinez-Carranza https://doi.org/10.1080/01431161.2019.1681601
9. A new productive framework for point‐based matching of oblique aircraft and UAV‐based images S. Bas & A. Ok https://doi.org/10.1111/phor.12374
10. Learning Dense Consistent Features for Aerial-to-Ground Structure-From-Motion H. Li et al. https://doi.org/10.1109/JSTARS.2023.3279199
11. Improving Details of Building Façades in Open LiDAR Data Using Ground Images S. Zhang et al. https://doi.org/10.3390/rs11040420
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13. Dense Stereo Matching Strategy for Oblique Images That Considers the Plane Directions in Urban Areas J. Liu et al. https://doi.org/10.1109/TGRS.2020.2972312
14. Stable least-squares matching for oblique images using bound constrained optimization and a robust loss function H. Hu et al. https://doi.org/10.1016/j.isprsjprs.2016.03.019
15. 3-D Point-Guided Aerial–Ground Image Matching for Robust Multiview Reconstruction Y. Xiao et al. https://doi.org/10.1109/JSTARS.2025.3616417
16. A New Multi-Criteria Tie Point Filtering Approach to Increase the Accuracy of UAV Photogrammetry Models V. Mousavi et al. https://doi.org/10.3390/drones6120413
17. Tie Point Matching between Terrestrial and Aerial Images Based on Patch Variational Refinement J. Liu et al. https://doi.org/10.3390/rs15040968
18. Select-and-Combine (SAC): A Novel Multi-stereo Depth Fusion Algorithm for Point Cloud Generation via Efficient Local Markov Netlets M. Elhashash & R. Qin https://doi.org/10.1109/TGRS.2023.3303179
19. A Novel Object-Level Building-Matching Method across 2D Images and 3D Point Clouds Based on the Signed Distance Descriptor (SDD) C. Zhao et al. https://doi.org/10.3390/rs15122974
20. LOD2 Building Generation Experiences and Comparisons I. Pârvu et al. https://doi.org/10.2478/jaes-2018-0019
21. Deep learning based multi-view stereo matching and 3D scene reconstruction from oblique aerial images J. Liu et al. https://doi.org/10.1016/j.isprsjprs.2023.08.015
22. Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management D. Giordan et al. https://doi.org/10.5194/nhess-18-1079-2018
23. MVSE-3D: multi-view semantic edge optimization for precision recovery of 3D building geometry H. He et al. https://doi.org/10.1080/17538947.2026.2616991
24. Robust 3-D Plane Segmentation From Airborne Point Clouds Based on Quasi-A-Contrario Theory X. Zhu et al. https://doi.org/10.1109/JSTARS.2021.3093576
25. Robust Fusion of Multi-Source Images for Accurate 3D Reconstruction of Complex Urban Scenes Y. Liang et al. https://doi.org/10.3390/rs15225302
26. Detecting Building Changes between Airborne Laser Scanning and Photogrammetric Data Z. Zhang et al. https://doi.org/10.3390/rs11202417
27. Scale invariant line-based co-registration of multimodal aerial data using L1 minimization of spatial and angular deviations P. Polewski & W. Yao https://doi.org/10.1016/j.isprsjprs.2019.04.004
28. Robust registration of aerial and close‐range photogrammetric point clouds using visual context features and scale consistency G. Chu et al. https://doi.org/10.1049/ipr2.12821
29. Field techniques for measuring bedrock erosion and denudation J. Turowski & K. Cook https://doi.org/10.1002/esp.4007
30. A Descriptor-less Well-Distributed Feature Matching Method Using Geometrical Constraints and Template Matching H. Mohammed & N. El-Sheimy https://doi.org/10.3390/rs10050747
31. Exterior orientation estimation of oblique aerial images using SfM-based robust bundle adjustment S. Verykokou & C. Ioannidis https://doi.org/10.1080/01431161.2020.1755737
32. Complete Scene Reconstruction by Merging Images and Laser Scans X. Gao et al. https://doi.org/10.1109/TCSVT.2019.2943892
33. CRBeDaSet: A Benchmark Dataset for High Accuracy Close Range 3D Object Reconstruction G. Gabara & P. Sawicki https://doi.org/10.3390/rs15041116
34. Building Extraction at Amodal-Instance- Segmentation Level: Datasets and Framework Y. Yan et al. https://doi.org/10.1109/TGRS.2023.3345867
35. UnDER: Unsupervised Dense Point Cloud Extraction Routine for UAV Imagery Using Deep Learning J. Bergado & F. Nex https://doi.org/10.3390/rs17010024
36. HiDeGS: High-frequency detail-enhanced Gaussian splatting for UAV multi-view reconstruction J. Song et al. https://doi.org/10.1016/j.jag.2026.105336
37. Simulating a Hybrid Acquisition System for UAV Platforms B. Alsadik et al. https://doi.org/10.3390/drones6110314
38. Automatic extraction of building geometries based on centroid clustering and contour analysis on oblique images taken by unmanned aerial vehicles L. Zhang et al. https://doi.org/10.1080/13658816.2021.1937632
39. An Oblique-Robust Absolute Visual Localization Method for GPS-Denied UAV With Satellite Imagery Y. Chen & J. Jiang https://doi.org/10.1109/TGRS.2023.3342142
40. Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas B. Wu et al. https://doi.org/10.1016/j.isprsjprs.2018.03.004
41. Fast Automatic Registration of UAV Images via Bidirectional Matching X. Luo et al. https://doi.org/10.3390/s23208566
42. SemanticMesh: parameterized fusion of semantic components for photogrammetric meshes L. Wang et al. https://doi.org/10.1080/10095020.2024.2381592
43. Virtual forests: a review on emerging questions in the use and application of 3D data in forestry A. Murtiyoso et al. https://doi.org/10.1080/14942119.2023.2217065
44. End-to-end multiview fusion for building mapping from aerial images Q. Chen et al. https://doi.org/10.1016/j.inffus.2024.102498
45. Challenges and advancements in image-based 3D reconstruction of large-scale urban environments: a review of deep learning and classical methods A. Akhavi Zadegan et al. https://doi.org/10.3389/fcomp.2025.1467103
46. Automatic Workflow for Roof Extraction and Generation of 3D CityGML Models from Low-Cost UAV Image-Derived Point Clouds A. Murtiyoso et al. https://doi.org/10.3390/ijgi9120743
47. Influence of the Inclusion of Off-Nadir Images on UAV-Photogrammetry Projects from Nadir Images and AGL (Above Ground Level) or AMSL (Above Mean Sea Level) Flights F. Agüera-Vega et al. https://doi.org/10.3390/drones8110662
48. Oblique aerial images: a review focusing on georeferencing procedures S. Verykokou & C. Ioannidis https://doi.org/10.1080/01431161.2018.1444294
49. Toward a unified theoretical framework for photogrammetry J. Shan et al. https://doi.org/10.1080/10095020.2020.1730712
50. Optimal Self-Calibration Strategies in the Combined Bundle Adjustment of Aerial–Terrestrial Integrated Images L. Xie et al. https://doi.org/10.3390/rs14091969
51. An Overview on Image-Based and Scanner-Based 3D Modeling Technologies S. Verykokou & C. Ioannidis https://doi.org/10.3390/s23020596
52. Review: 3D printing of ceramics using direct ink writing A. Kumar et al. https://doi.org/10.1007/s10853-026-13774-w
53. Structure-aware completion of photogrammetric meshes in urban road environment Q. Zhu et al. https://doi.org/10.1016/j.isprsjprs.2021.02.010
54. Mapping with Pléiades—End-to-End Workflow R. Perko et al. https://doi.org/10.3390/rs11172052
55. Lattice-Point Mutually Guided Ground-to-Aerial Feature Matching for Urban Scene Images X. Zheng et al. https://doi.org/10.1109/JSTARS.2021.3069222
56. Aerial–Terrestrial Image Feature Matching: An Evaluation of Recent Deep Learning Methods H. Wang et al. https://doi.org/10.1109/JSTARS.2025.3564326
57. Air-to-Ground Registration of Point Clouds for Urban Scenes Using Dual Gravity Lines N. Xu & R. Qin https://doi.org/10.1109/TGRS.2026.3665399
58. Uncertainty quantification framework for aerial and UAV photogrammetry through error propagation D. Huang & R. Qin https://doi.org/10.1016/j.isprsjprs.2026.04.047
59. Enhancing UAV–SfM 3D Model Accuracy in High-Relief Landscapes by Incorporating Oblique Images P. Nesbit & C. Hugenholtz https://doi.org/10.3390/rs11030239
60. Photogrammetric Measurement of a Wooden Truss M. Marčiš & M. Fraštia https://doi.org/10.2478/sjce-2018-0022
61. Object-Based Semi-global Multi-image Matching F. Bethmann & T. Luhmann https://doi.org/10.1007/s41064-017-0034-z
62. Information from imagery: ISPRS scientific vision and research agenda J. Chen et al. https://doi.org/10.1016/j.isprsjprs.2015.09.008
63. An asymmetric re-weighting method for the precision combined bundle adjustment of aerial oblique images L. Xie et al. https://doi.org/10.1016/j.isprsjprs.2016.03.017
64. Automated Registration of SfM‐MVS Multitemporal Datasets Using Terrestrial and Oblique Aerial Images L. Parente et al. https://doi.org/10.1111/phor.12346
65. Shape Reconstruction of Object-Level Building From Single Image Based on Implicit Representation Network C. Zhao et al. https://doi.org/10.1109/LGRS.2021.3126767
66. Reconstruction of LoD-2 Building Models Guided by Façade Structures from Oblique Photogrammetric Point Cloud F. Wang et al. https://doi.org/10.3390/rs15020400
67. IMGTR: Image-triangle based multi-view 3D reconstruction for urban scenes Z. Hu et al. https://doi.org/10.1016/j.isprsjprs.2021.09.009
68. UseGeo - A UAV-based multi-sensor dataset for geospatial research F. Nex et al. https://doi.org/10.1016/j.ophoto.2024.100070
69. StructuredMesh: 3-D Structured Optimization of Façade Components on Photogrammetric Mesh Models Using Binary Integer Programming L. Wang et al. https://doi.org/10.1109/TGRS.2023.3348492
70. Aerial-ground image feature matching via 3D Gaussian splatting-based intermediate view rendering J. Yu et al. https://doi.org/10.1080/10095020.2026.2658226
71. Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring M. Kulicki et al. https://doi.org/10.1007/s40725-024-00234-4
72. Assessing spatiotemporal land dynamics using Google Earth Engine and random forest: trends and drivers of change in Ethiopia’s fragile Jema River Basin T. Selamu et al. https://doi.org/10.1007/s10661-026-15502-y
73. Joint 3D reconstruction of aerial and terrestrial imagery for complete building reconstruction P. Wei et al. https://doi.org/10.1016/j.jobe.2025.114351
74. Towards Semantic Photogrammetry: Generating Semantically Rich Point Clouds from Architectural Close-Range Photogrammetry A. Murtiyoso et al. https://doi.org/10.3390/s22030966
75. Multiplatform Bundle Adjustment Method Supported by Object Structural Information J. Liu & W. Guo https://doi.org/10.1109/JSTARS.2023.3339293
76. Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation X. Wang et al. https://doi.org/10.1016/j.isprsjprs.2018.11.009
77. Oblique aerial image matching based on iterative simulation and homography evaluation W. Song et al. https://doi.org/10.1016/j.patcog.2018.10.027
78. Evolutionary Optimization for Robust Epipolar-Geometry Estimation and Outlier Detection M. Shahbazi et al. https://doi.org/10.3390/a10030087
79. A Vision-Based Motion Control Framework for Water Quality Monitoring Using an Unmanned Aerial Vehicle F. Panetsos et al. https://doi.org/10.3390/su14116502
80. Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects T. Xiang et al. https://doi.org/10.1109/MGRS.2019.2918840