Author:
Li Pan,Wu Suping,Zhang Xitie,Peng Yuxin,Zhang Boyang,Wang Bin
Publisher
Springer Nature Switzerland
Reference31 articles.
1. Khot, T., Agrawal, S., Tulsiani, S., Mertz, C., Lucey, S., Hebert, M.: Learning unsupervised multi-view stereopsis via robust photometric consistency. arXiv:abs/1905.02706 (2019)
2. Yao, Y., Luo, Z., Li, S., Shen, T., Fang, T., Quan, L.: Recurrent mvsnet for high-resolution multi-view stereo depth inference, pp. 5520–5529 (2019)
3. Ji, M., Gall, J., Zheng, H., Liu, Y., Fang, L.: Surfacenet: an end-to-end 3D neural network for multiview stereopsis. In: IEEE International Conference on Computer Vision (ICCV), pp. 2326–2334 (2017)
4. Xue, Y., et al.: MVSCRF: learning multi-view stereo with conditional random fields. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 4311–4320 (2019)
5. Yu, Z., Gao, S.: Fast-mvsnet: sparse-to-dense multi-view stereo with learned propagation and gauss-newton refinement. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1946–1955 (2020)