4.7 Article

Deep Learning Advances in Computer Vision with 3D Data: A Survey

Journal

ACM COMPUTING SURVEYS
Volume 50, Issue 2, Pages -

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3042064

Keywords

3D data; 3D object recognition; 3D object retrieval; 3D segmentation; convolutional neural networks; deep learning

Funding

  1. EU Horizon Programme [H2020/2015-2018, 665066]
  2. H2020 Societal Challenges Programme [665066] Funding Source: H2020 Societal Challenges Programme

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Deep learning has recently gained popularity achieving state-of-the-art performance in tasks involving text, sound, or image processing. Due to its outstanding performance, there have been efforts to apply it in more challenging scenarios, for example, 3D data processing. This article surveys methods applying deep learning on 3D data and provides a classification based on how they exploit them. From the results of the examined works, we conclude that systems employing 2D views of 3D data typically surpass voxel-based (3D) deep models, which however, can perform better with more layers and severe data augmentation. Therefore, larger-scale datasets and increased resolutions are required.

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