Staszak, RafałMichałek, PiotrChudziński, JakubKopicki, MarekBelter, Dominik2023-09-212023-09-212023Staszak R., Michałek P., Chudziński J., Kopicki M., Belter D., 3D Reconstruction of Non-Visible Surfaces of Objects from a Single Depth View – Comparative Study. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 19-24, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.1.978-83-66741-92-8http://hdl.handle.net/11652/4776https://doi.org/10.34658/9788366741928.1Scene and object reconstruction is an important problem in robotics, in particular in planning collision-free trajectories or in object manipulation. This paper compares two strategies for the reconstruction of nonvisible parts of the object surface from a single RGB-D camera view. The first method, named DeepSDF predicts the Signed Distance Transform to the object surface for a given point in 3D space. The second method, named MirrorNet reconstructs the occluded objects’ parts by generating images from the other side of the observed object. Experiments performed with objects from the ShapeNet dataset, show that the view-dependent MirrorNet is faster and has smaller reconstruction errors in most categories.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionroboticsscene reconstructionneural scene representationrobotykarekonstrukcja scenreprezentacja scen neuronowychRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.1