Related papers: Attention-based Point Cloud Edge Sampling

Attention-based Point Cloud Edge Sampling

URL: http://arxiv.org/abs/2302.14673v2
Date: Sun, 26 Mar 2023 14:32:23 GMT
Title: Attention-based Point Cloud Edge Sampling
Authors: Chengzhi Wu, Junwei Zheng, Julius Pfrommer, J\"urgen Beyerer
Abstract summary: Point cloud sampling is a less explored research topic for this data representation. This paper proposes a non-generative Attention-based Point cloud Edge Sampling method (APES) Both qualitative and quantitative experimental results show the superior performance of our sampling method on common benchmark tasks.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Point cloud sampling is a less explored research topic for this data representation. The most commonly used sampling methods are still classical random sampling and farthest point sampling. With the development of neural networks, various methods have been proposed to sample point clouds in a task-based learning manner. However, these methods are mostly generative-based, rather than selecting points directly using mathematical statistics. Inspired by the Canny edge detection algorithm for images and with the help of the attention mechanism, this paper proposes a non-generative Attention-based Point cloud Edge Sampling method (APES), which captures salient points in the point cloud outline. Both qualitative and quantitative experimental results show the superior performance of our sampling method on common benchmark tasks.

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