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A Novel Equivariant Self-Supervised Vector Network for Three-Dimensional Point Clouds

For networks that process 3D data, estimating the orientation and position of 3D objects is a challenging task. This is because the traditional networks are not robust to the rotation of the data, and their internal workings are largely opaque and uninterpretable. To solve this problem, a novel equi...

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Gorde:
Xehetasun bibliografikoak
Egile Nagusiak: Kedi Shen, Jieyu Zhao, Min Xie
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2025-03-01
Saila:Algorithms
Gaiak:
Sarrera elektronikoa:https://www.mdpi.com/1999-4893/18/3/152
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