资源分类
》 资源 》论文》3D Point Capsule Networks

3D Point Capsule Networks

2019-09-17 | |  75 |   44 |   0 0 0
Abstract In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our uni- fied formulation of the common 3D auto-encoders. The dynamic routing scheme [30] and the peculiar 2D latent space deployed by our capsule networks bring in improvements for several common point cloud-related tasks, such as object classification, object reconstruction and part segmentation as substantiated by our extensive evaluations. Moreover, it enables new applications such as part interpolation and replacement.

上一篇：Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph

下一篇：A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...