Tangent Convolutions for Dense Prediction in 3D

• Published in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition pp. 3887 - 3896
• Main Authors: Tatarchenko, Maxim, Park, Jaesik, Koltun, Vladlen, Zhou, Qian-Yi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Convolution; Geometry; Kernel; Semantics; Shape; Three-dimensional displays; Two dimensional displays

We present an approach to semantic scene analysis using deep convolutional networks. Our approach is based on tangent convolutions - a new construction for convolutional networks on 3D data. In contrast to volumetric approaches, our method operates directly on surface geometry. Crucially, the constr...