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Stereo reconstruction models trained on small images do not generalize well to high-resolution data.
D. Scharstein, H. Hirschmüller, Y. Kitajima, G. Krathwohl, N. Nešić, X. Wang, and P. Westling, “High-resolution stereo datasets with subpixel-accurate ground truth,” in German conference on pattern recognition . Springer, 2014, pp. 31–42
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A. Kendall, H. Martirosyan, S. Dasgupta, P. Henry, R. Kennedy, A. Bachrach, and A. Bry, “End-to-end learning of geometry and context for deep stereo regression,” in ICCV , Oct 2017
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J.-R. Chang and Y.-S. Chen, “Pyramid stereo matching network,” in CVPR , 2018, pp. 5410–5418
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Y. Yao, Z. Luo, S. Li, T. Fang, and L. Quan, “Mvsnet: Depth inference for unstructured multi-view stereo,” in ECCV , 2018
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S. Khamis, S. Fanello, C. Rhemann, A. Kowdle, J. Valentin, and S. Izadi, “Stereonet: Guided hierarchical refinement for real-time edge-aware depth prediction,” in ECCV , 2018, pp. 573–590
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Z. Jie, P. Wang, Y. Ling, B. Zhao, Y. Wei, J. Feng, and W. Liu, “Left-right comparative recurrent model for stereo matching,” in CVPR , 2018, pp. 3838–3846
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Y. Wang, Y. Yang, Z. Yang, L. Zhao, P. Wang, and W. Xu, “Occlusion aware unsupervised learning of optical flow,” in CVPR , 2018
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A. Li and Z. Yuan, “Occlusion aware stereo matching via cooperative unsupervised learning,” in Asian Conference on Computer Vision . Springer, 2018, pp. 197–213
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E. Ilg, T. Saikia, M. Keuper, and T. Brox, “Occlusions, motion and depth boundaries with a generic network for disparity, optical flow or scene flow estimation,” in ECCV , 2018
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2018
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G. Yang, J. Manela, M. Happold, and D. Ramanan, “Hierarchical deep stereo matching on high-resolution images,” in CVPR , 2019
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H. Xu and J. Zhang, “Aanet: Adaptive aggregation network for efficient stereo matching,” in CVPR , 2020
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G. Yang, X. Song, C. Huang, Z. Deng, J. Shi, and B. Zhou, “Drivingstereo: A large-scale dataset for stereo matching in autonomous driving scenarios,” in CVPR , 2019
2019
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R. Chen, S. Han, J. Xu, and H. Su, “Point-based multi-view stereo network,” in ICCV , 2019
2019
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Y. Yao, Z. Luo, S. Li, T. Shen, T. Fang, and L. Quan, “Recurrent mvsnet for high-resolution multi-view stereo depth inference,” in CVPR , 2019
2019
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G.-Y. Nie, M.-M. Cheng, Y. Liu, Z. Liang, D.-P. Fan, Y. Liu, and Y. Wang, “Multi-level context ultra-aggregation for stereo matching,” in CVPR , 2019
2019
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X. Guo, K. Yang, W. Yang, X. Wang, and H. Li, “Group-wise correlation stereo network,” in CVPR , 2019
2019
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F. Zhang, V. Prisacariu, R. Yang, and P. H. Torr, “Ga-net: Guided aggregation net for end-to-end stereo matching,” in CVPR , 2019
2019
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S. Duggal, S. Wang, W.-C. Ma, R. Hu, and R. Urtasun, “Deeppruner: Learning efficient stereo matching via differentiable patchmatch,” in ICCV , 2019
2019
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2020
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S. Zhao, Y. Sheng, Y. Dong, E. I.-C. Chang, and Y. Xu, “Maskflownet: Asymmetric feature matching with learnable occlusion mask,” in CVPR , 2020
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A. Badki, A. Troccoli, K. Kim, J. Kautz, P. Sen, and O. Gallo, “Bi3d: Stereo depth estimation via binary classifications,” in CVPR , 2020
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M. Yang, F. Wu, and W. Li, “Waveletstereo: Learning wavelet coefficients of disparity map in stereo matching,” in CVPR , 2020
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2020
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Z. Bai, Z. Cui, J. A. Rahim, X. Liu, and P. Tan, “Deep facial non-rigid multi-view stereo,” in CVPR , 2020
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W. Zhen, Y. Hu, H. Yu, and S. Scherer, “Lidar-enhanced structure-from-motion,” in ICRA . IEEE, 2020, pp. 6773–6779
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