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Guobiao Yao, Jin Zhang, Jianya Gong and Fengxiang Jin
To promote the development of deep learning for feature matching, image registration, and three-dimensional reconstruction, we propose a method of constructing a deep learning benchmark dataset for affine-invariant feature matching. Existing images often...
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Paulina Zachar, Wojciech Ostrowski, Anna Platek-Zak and Zdzislaw Kurczynski
The dynamic development of deep learning methods in recent years has prompted the widespread application of these algorithms in the field of photogrammetry and remote sensing, especially in the areas of image recognition, classification, and object detec...
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Arnadi Murtiyoso, Mirza Veriandi, Deni Suwardhi, Budhy Soeksmantono and Agung Budi Harto
Developments in UAV sensors and platforms in recent decades have stimulated an upsurge in its application for 3D mapping. The relatively low-cost nature of UAVs combined with the use of revolutionary photogrammetric algorithms, such as dense image matchi...
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Jingxue Wang, Ning Zhang, Xiangqian Wu and Weixi Wang
Reliable image matching is the basis of image-based three-dimensional (3D) reconstruction. This study presents a quasi-dense matching method based on triangulation constraint and propagation as applied to different types of close-range image matching, su...
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Damian Wierzbicki and Marcin Nienaltowski
In the last few years, Unmanned Aerial Vehicles (UAVs) equipped with compact digital cameras, have become a cheap and efficient alternative to classic aerial photogrammetry and close-range photogrammetry. Low-altitude photogrammetry has great potential n...
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Florent Poux, Romain Neuville, Line Van Wersch, Gilles-Antoine Nys and Roland Billen
Digital investigations of the real world through point clouds and derivatives are changing how curators, cultural heritage researchers and archaeologists work and collaborate. To progressively aggregate expertise and enhance the working proficiency of al...
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