PointListNet: Deep Learning on 3D Point Lists
Hehe Fan, Linchao Zhu, Yi Yang, Mohan S. Kankanhalli
Abstract
A sentence is a list of words. (a) text: 1D word list (b) image: 2D pixel grid (c) 3D point cloud/set (d) protein: 3D point list Figure 1. Data structure comparison of text, image, point cloud and protein. (a) Texts are regular 1D lists of words. The position is the word's sequential order in the text and the feature is the word itself. (b) Images are regular 2D grids of pixels. The position is the row and column where the pixel is located and the feature is the color. (c) Point clouds are irregular 3D point sets. The position is the 3D coordinate and the feature is the point attributes. (d) Proteins can be seen as 3D point lists. The position of an amino acid involves a regular 1D sequential order and an irregular 3D coordinate. The feature is the amino acid (residue) type.
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Cited by top-tier papers2
- Clustering for Protein Representation LearningRuijie Quan, Wenguan Wang, Fan Ma, Hehe Fan et al.CVPR 2024 · 10 citations
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Builds on13
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn et al.ICLR 2021 · 21,477 citations
- KPConv: Flexible and Deformable Convolution for Point CloudsHugues Thomas, Charles R. Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui et al.ICCV 2019 · 3,193 citations
- Deep Hough Voting for 3D Object Detection in Point CloudsCharles R. Qi, Or Litany, Kaiming He, Leonidas J. GuibasICCV 2019 · 1,467 citations
- Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP FrameworkXu Ma, Can Qin, Haoxuan You, Haoxi Ran et al.ICLR 2022 · 841 citations
- Learning from Protein Structure with Geometric Vector PerceptronsBowen Jing, Stephan Eismann, Patricia Suriana, Raphael John Lamarre Townshend et al.ICLR 2021 · 627 citations
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