Robust Point Cloud Processing through Positional Embedding
Published in arXiv (Cornell University) • Sep 1, 2023
NobleIDNI8P68W29R92S65
Authors:,,
Jianqiao Zheng
Xue-Qian Li
Sameera Ramasinghe
Abstract
End-to-end trained per-point embeddings are an essential ingredient of any state-of-the-art 3D point cloud processing such as detection or alignment. Methods like PointNet, or the more recent point cloud transformer -- and its variants -- all employ learned per-point embeddings. Despite impressive p...
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