3D Convolution Channel Compression for Stereo Matching
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5591-2_5
Reference16 articles.
1. Liang, Z., Guo, Y., Feng, Y., et al.: Stereo matching using multi-level cost volume and multi-scale feature constancy. IEEE Trans. Pattern Anal. Mach. Intell. 43(1), 300–315 (2021)
2. Mayer, N., Ilg, E., Häusser, P., Fischer, P., Cremers, D., et al.: A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp. 4040–4048 (2016)
3. Xu, H., et al.: Aanet: adaptive aggregation network for efficient stereo matching. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1956–1965 (2020)
4. Chang, J.R., Chen, Y.S.: Pyramid stereo matching network. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 5410–5418 (2018)
5. Guo, X., Yang, K., Yang, W., et al.: Group-wise correlation stereo network. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3268–3277 (2019)
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