1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I.J., Harp, A., Irving, G., Isard, M., Jia, Y., Józefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D.G., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P.A., Vanhoucke, V., Vasudevan, V., Viégas, F.B., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X., 2016. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. CoRR abs/1603.04467. http://arxiv.org/abs/1603.04467.
2. Atienza, R., 2018. Fast disparity estimation using dense networks. In: IEEE International Conference on Robotics and Automation ICRA. pp. 3207–3212.
3. Batsos, K., Mordohai, P., 2018. Recresnet: A recurrent residual cnn architecture for disparity map enhancement. In: International Conference on 3D Vision. pp. 238–247.
4. Bleyer, M., Rhemann, C., Rother, C., 2011. Patchmatch stereo - stereo matching with slanted support windows. In: British Machine Vision Conference. pp. 1–11.
5. Bosch, M., Foster, K., Christie, G., Wang, S., Hager, G.D., Brown, M., 2019. Semantic stereo for incidental satellite images. In: IEEE Winter Conference on Applications of Computer Vision. pp. 1524–1532.