The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Deep Learning Advances in Computer Vision with 3D Data: A Survey
Open accessAbstract
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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Cited by
Deep Learning in Mobile and Wireless Networking: A Survey
Zhang, C., Patras, P., & Haddadi, H. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2904897 · Cited by 1,768
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey of Datasets and Methods
Gao, B., Pan, Y., Li, C., Geng, S., & Zhao, H. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3076844 · Cited by 105
Guo, J., Zhang, W., Fan, W., & Li, W. (2018) · Journal of Management Information Systems · doi:10.1080/07421222.2018.1523564 · Cited by 85
Metadata
- Authors
- Ioannidou, A., Chatzilari, E., Nikolopoulos, S., & Kompatsiaris, I.
- Venue
- ACM Computing Surveys
- Published
- 2017-04-06
- Volume
- 50
- Issue
- 2
- Pages
- 1-38
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2604249033
- Cited by
- 327
- References
- 36
- FWCI
- 13.59
- Type
- journal article
- Language
- en
- Open access
- green
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