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cs.CV2020
DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes
Jonas Schult, Francis Engelmann, Theodora Kontogianni +1
We propose DualConvMesh-Nets (DCM-Net) a family of deep hierarchical convolutional networks over 3D geometric data that combines two types of convolutions. The first type, geodesic…
cs.CV2019
3D-BEVIS: Bird's-Eye-View Instance Segmentation
Cathrin Elich, Francis Engelmann, Theodora Kontogianni +1
Recent deep learning models achieve impressive results on 3D scene analysis tasks by operating directly on unstructured point clouds. A lot of progress was made in the field of obj…
cs.CV2018
Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds
Francis Engelmann, Theodora Kontogianni, Jonas Schult +1
In this paper, we present a deep learning architecture which addresses the problem of 3D semantic segmentation of unstructured point clouds. Compared to previous work, we introduce…