Point Transformer

نویسندگان

چکیده

In this work, we present Point Transformer, a deep neural network that operates directly on unordered and unstructured point sets. We design Transformer to extract local global features relate both representations by introducing the local-global attention mechanism, which aims capture spatial relations shape information. For purpose, propose SortNet, as part of induces input permutation invariance selecting points based learned score. The output is sorted invariant feature list can be incorporated into common computer vision applications. evaluate our approach standard classification segmentation benchmarks demonstrate competitive results compared prior work. Code publicly available at: https://github.com/engelnico/point-transformer

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2021

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2021.3116304