Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Our network architecture for segmentationAbstract
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks - part-level segmentation of 3D shapes and 3D reconstruc- tion from single view images. Ten teams have participated in the challenge and the best performing teams have out- performed state-of-the-art approaches on both tasks. A few novel deep learning architectures have been proposed on various 3D representations on both tasks. We report the techniques used by each team and the corresponding per- formances. In addition, we summarize the major discov- eries from the reported results and possible trends for the future work in the field.
Type
Publication
arXiv
