The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Monocular depth estimation with hierarchical fusion of dilated CNNs and soft-weighted-sum inference
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“Together, these contributions yield state-of-the-art monocular and stereo self-supervised depth estimation results on the KITTI dataset [13], and simplify many components found in the existing top performing models.”
From Digging Into Self-Supervised Monocular Depth Estimation (2019) · cites this paper as [13]
Citations
Cites
Deep Residual Learning for Image Recognition
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Very Deep Convolutional Networks for Large-Scale Image Recognition
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ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699184 · Cited by 22,392
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
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Are we ready for autonomous driving? The KITTI vision benchmark suite
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Proceedings of IEEE International Conference on Computer Vision
(1995) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1995.466933 · Cited by 13,117
Fully convolutional networks for semantic segmentation
Shelhamer, E., Long, J., & Darrell, T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2572683 · Cited by 11,898
Multi-scale context aggregation by dilated convolutions
Yu, F., & Koltun, V. (2015) · arXiv · doi:10.48550/arxiv.1511.07122 · Cited by 7,738
Indoor segmentation and support inference from rgbd images
Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760
Cited by
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Digging Into Self-Supervised Monocular Depth Estimation
Godard, C., Aodha, O. M., Firman, M., & Brostow, G. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00393 · Cited by 2,561
Xu, D., Ouyang, W., Wang, X., & Sebe, N. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00077 · Cited by 551
Monocular human pose estimation: A survey of deep learning-based methods
Chen, Y., Tian, Y., & He, M. (2020) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.102897 · Cited by 479
Self-citationTolan, J., Yang, H.-I., Nosarzewski, B., Couairon, G., Vo, H. V., Brandt, J., Spore, J., Majumdar, S., Haziza, D., Vamaraju, J., et al. (2024) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113888 · Cited by 419
Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation
Xu, D., Wang, W., Tang, H., Liu, H., Sebe, N., & Ricci, E. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00412 · Cited by 358
Metadata
- Authors
- Li, B., Dai, Y., & He, M.
- Affiliations
- Northwestern Polytechnical University (CN)
- Corresponding author
- Dai, Yuchao
- He, Mingyi
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 83
- Pages
- 328-339
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2964193874
- Cited by
- 142
- References
- 45
- Citations by year
- 2025: 7 · 2024: 12 · 2023: 12 · 2022: 18 · 2021: 21 · 2020: 31 · 2019: 33 · 2018: 8
- FWCI
- 11.38
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Pattern Recognition (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Natural Science Foundation of China (61420106007, 61671387)
- Australian Research Council (DE140100180)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Engineering › Media Technology › Image Processing Techniques and Applications
- Keywords
- monocular depth estimation, dilated convolutional neural network, hierarchical feature fusion, quantization error reduction, semantic segmentation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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