ResSANet: Learning Geometric Information for Point Cloud Processing

Point clouds with rich local geometric information have potentially huge implications in several applications, especially in areas of robotic manipulation and autonomous driving. However, most point cloud processing methods cannot extract enough geometric features from a raw point cloud, which restr...

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Detalles Bibliográficos
Autores principales: Zhu, Xiaojun, Zhang, Zheng, Ruan, Jian, Liu, Houde, Sun, Hanxu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124999/
https://www.ncbi.nlm.nih.gov/pubmed/34066612
http://dx.doi.org/10.3390/s21093227

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124999/
https://www.ncbi.nlm.nih.gov/pubmed/34066612
http://dx.doi.org/10.3390/s21093227

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