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Resolution-Free Point Cloud Sampling Network with Data Distillation

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13662))

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Abstract

Down-sampling algorithms are adopted to simplify the point clouds and save the computation cost on subsequent tasks. Existing learning-based sampling methods often need to train a big sampling network to support sampling under different resolutions, which must generate sampled points with the costly maximum resolution even if only low-resolution points need to be sampled. In this work, we propose a novel resolution-free point clouds sampling network to directly sample the original point cloud to different resolutions, which is conducted by optimizing non-learning-based initial sampled points to better positions. Besides, we introduce data distillation to assist the training process by considering the differences between task network outputs from original point clouds and sampled points. Experiments on point cloud reconstruction and recognition tasks demonstrate that our method can achieve SOTA performances with lower time and memory cost than existing learning-based sampling strategies. Codes are available at https://github.com/Tianxinhuang/PCDNet.

T. Huang and J. Zhang—Indicates equal contributions.

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Acknowledgement

We thank all authors, reviewers and the chair for the excellent contributions. This work is supported by the National Science Foundation 62088101.

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Authors and Affiliations

  1. APRIL Lab, Zhejiang University, Hangzhou, China

    Tianxin Huang, Jiangning Zhang, Jun Chen, Yuang Liu & Yong Liu

  2. Tencent Youtu Laboratory, Shanghai, China

    Jiangning Zhang

  3. Huzhou Institute of Zhejiang University, Huzhou, China

    Yong Liu

Authors
  1. Tianxin Huang
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  2. Jiangning Zhang
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  3. Jun Chen
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  4. Yuang Liu
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  5. Yong Liu
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Corresponding author

Correspondence to Yong Liu .

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Editors and Affiliations

  1. Tel Aviv University, Tel Aviv, Israel

    Shai Avidan

  2. University College London, London, UK

    Gabriel Brostow

  3. Google AI, Accra, Ghana

    Moustapha Cissé

  4. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  5. Facebook (United States), Menlo Park, CA, USA

    Tal Hassner

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Huang, T., Zhang, J., Chen, J., Liu, Y., Liu, Y. (2022). Resolution-Free Point Cloud Sampling Network with Data Distillation. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13662. Springer, Cham. https://doi.org/10.1007/978-3-031-20086-1_4

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  • DOI: https://doi.org/10.1007/978-3-031-20086-1_4

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  • Online ISBN: 978-3-031-20086-1

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