Guided aggregation and disparity refinement for real-time stereo matching-Reference-Cited by-同舟云学术

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Guided aggregation and disparity refinement for real-time stereo matching

Published:2024-03-11 Issue:5 Volume:18 Page:4467-4477
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Yang Jinlong,Wu Cheng,Wang Gang,Chen Dong

Funder

Natural Science Foundation of Jiangsu Province

Engineering Research Center of Integration and Application of Digital Learning Technology, Ministry of Education

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-024-03087-3.pdf

Reference35 articles.

1. Scharstein, D., Hirschmüller, H., Kitajima, Y., Krathwohl, G., Nesic, N., Wang, X., Westling, P.: High-resolution stereo datasets with subpixel-accurate ground truth. In: Pattern Recognition - 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014, Proceedings, vol. 8753, pp. 31–42 (2014). https://doi.org/10.1007/978-3-319-11752-2_3

2. Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? The Kitti vision benchmark suite. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 3354–3361 (2012). https://doi.org/10.1109/CVPR.2012.6248074

3. Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions using graph cuts. In: Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, vol. 2, pp. 508–5152 (2001). https://doi.org/10.1109/ICCV.2001.937668

4. Sun, J., Zheng, N.-N., Shum, H.-Y.: Stereo matching using belief propagation. IEEE Trans. Pattern Anal. Mach. Intell. 25(7), 787–800 (2003). https://doi.org/10.1109/TPAMI.2003.1206509

5. Yoon, K.-J., Kweon, I.S.: Adaptive support-weight approach for correspondence search. IEEE Trans. Pattern Anal. Mach. Intell. 28(4), 650–656 (2006). https://doi.org/10.1109/TPAMI.2006.70

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