Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Reference80 articles.
1. Abdulwahab, S., Rashwan, H. A., Garcia, M. A., Masoumian, A., & Puig, D. (2022). Monocular depth map estimation based on a multi-scale deep architecture and curvilinear saliency feature boosting. Neural Computing and Applications, 34(19), 16423–16440.
2. Alhashim, I., & Wonka, P. (2018). High quality monocular depth estimation via transfer learning. arXiv preprint arXiv:1812.11941
3. Atapour-Abarghouei, A., & Breckon, T. P. (2018). Real-time monocular depth estimation using synthetic data with domain adaptation via image style transfer. In IEEE conference on computer vision and pattern recognition (CVPR) (pp. 2800–2810).
4. Bhat, S. F., Alhashim, I., & Wonka, P. (2021). Adabins: Depth estimation using adaptive bins. In IEEE conference on computer vision and pattern recognition (CVPR) (pp. 4009–4018).
5. Butler, D. J., Wulff, J., Stanley, G. B., & Black, M. J. (2012). A naturalistic open source movie for optical flow evaluation. In European conference on computer vision (ECCV) (pp. 611–625).