Point clouds provide a flexible geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices. While hand-designed features on point clouds have long been proposed in graphics and vision, however, the recent overwhelming success of convolutional neural networks (CNNs) for image analysis suggests the value of adapting insight from CNN to the point cloud world. Point clouds inherently lack topological information, so designing a model to recover topology can enrich the representation power of point clouds. To this end, we propose a new neural network module dubbedEdgeConvsuitable for CNN-based high-level tasks on point clouds, including classification and segmentation. EdgeConv acts on graphs dynamically computed in each layer of the network. It is differentiable and can be plugged into existing architectures. Compared to existing modules operating in extrinsic space or treating each point independently, EdgeConv has several appealing properties: It incorporates local neighborhood information; it can be stacked applied to learn global shape properties; and in multi-layer systems affinity in feature space captures semantic characteristics over potentially long distances in the original embedding. We show the performance of our model on standard benchmarks, including ModelNet40, ShapeNetPart, and S3DIS.

Yue Wang

Yongbin Sun

Ziwei Liu

Sanjay E. Sarma

Michael M. Bronstein

Justin M. Solomon

ACM Transactions on Graphics

ACM TRANSACTIONS ON GRAPHICS (TOG) 是一份经过同行评审的科学期刊，旨在传播计算机图形学领域的最新发现。它自 1982 年以来由计算机协会出版。从 2003 年开始，所有在 SIGGRAPH 年度会议上被接受发表的论文都印在该期刊的夏季特刊上。

ACM Transactions on Graphics (TOG) is a peer-reviewed scientific journal aimed at disseminating the latest research findings in the field of computer graphics. It has been published by the Association for Computing Machinery since 1982. Since 2003, all papers accepted for presentation at the SIGGRAPH annual conference are included in the summer issue of this journal.

《ACM Transactions on Graphics》（TOG）是一本经过同行评审的科学期刊，旨在传播计算机图形学领域的最新研究成果。该期刊自1982年由计算机协会出版。从2003年起，所有在SIGGRAPH年度会议上接受发表的论文均会收录在该期刊的夏季特刊中。

Category	Quartile
计算机科学	1
计算机科学, 计算机软件工程	1

Dynamic Graph CNN for Learning on Point Clouds

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Journal Info

Category	Quartile
COMPUTER SCIENCE, SOFTWARE ENGINEERING	1