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Contrastive Learning for 3D Point Clouds Classification and Shape Completion
In this paper, we present the idea of Self Supervised learning on the shape completion and classification of point clouds. Most 3D shape completion pipelines utilize AutoEncoders to extract features from point clouds used in downstream tasks such as classification, segmentation, detection, and other...
Autores principales: | Nazir, Danish, Afzal, Muhammad Zeshan, Pagani, Alain, Liwicki, Marcus, Stricker, Didier |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587100/ https://www.ncbi.nlm.nih.gov/pubmed/34770698 http://dx.doi.org/10.3390/s21217392 |
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