Web: http://arxiv.org/abs/2108.09228

May 6, 2022, 1:10 a.m. | Guoquan Xu, Hezhi Cao, Yifan Zhang, Jianwei Wan, Ke Xu, Yanxin Ma

cs.CV updates on arXiv.org arxiv.org

Recently, deep neural networks have made remarkable achievements in 3D point
cloud classification. However, existing classification methods are mainly
implemented on idealized point clouds and suffer heavy degradation of
per-formance on non-idealized scenarios. To handle this prob-lem, a feature
representation learning method, named Dual-Neighborhood Deep Fusion Network
(DNDFN), is proposed to serve as an improved point cloud encoder for the task
of non-idealized point cloud classification. DNDFN utilizes a trainable
neighborhood learning method called TN-Learning to capture the global key …

analysis arxiv cloud cv deep fusion network

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