SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification
Wang Y, Tan DJ, Navab N, Tombari F (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12348 LNCS
Pages Range: 70-85
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Glasgow, GBR
ISBN: 9783030585792
DOI: 10.1007/978-3-030-58580-8_5
Abstract
Point clouds are often the default choice for many applications as they exhibit more flexibility and efficiency than volumetric data. Nevertheless, their unorganized nature – points are stored in an unordered way – makes them less suited to be processed by deep learning pipelines. In this paper, we propose a method for 3D object completion and classification based on point clouds. We introduce a new way of organizing the extracted features based on their activations, which we name soft pooling. For the decoder stage, we propose regional convolutions, a novel operator aimed at maximizing the global activation entropy. Furthermore, inspired by the local refining procedure in Point Completion Network (PCN), we also propose a patch-deforming operation to simulate deconvolutional operations for point clouds. This paper proves that our regional activation can be incorporated in many point cloud architectures like AtlasNet and PCN, leading to better performance for geometric completion. We evaluate our approach on different 3D tasks such as object completion and classification, achieving state-of-the-art accuracy.
Involved external institutions
Ireland (IE)
Germany (DE)How to cite
APA:
Wang, Y., Tan, D.J., Navab, N., & Tombari, F. (2020). SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification. In Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 70-85). Glasgow, GBR: Springer Science and Business Media Deutschland GmbH.
MLA:
Wang, Yida, et al. "SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification." Proceedings of the 16th European Conference on Computer Vision, ECCV 2020, Glasgow, GBR Ed. Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm, Springer Science and Business Media Deutschland GmbH, 2020. 70-85.
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