Author:
Li Shaokang,Lyu Chengzhi,Xia Bin,Chen Ziheng,Zhang Lei
Funder
Foundation of Hubei Educational Committee
Natural Science Fund Project of Hubei Province
Publisher
Springer Science and Business Media LLC
Reference54 articles.
1. Andraghetti, L., Myriokefalitakis, P., Dovesi, P.L., et al.: Enhancing self-supervised monocular depth estimation with traditional visual odometry. In: 2019 International Conference on 3D Vision (3DV), pp. 424–433 (2019). https://doi.org/10.1109/3DV.2019.00054
2. Bae, J., Moon, S., Im, S.: Deep digging into the generalization of self-supervised monocular depth estimation. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 187–196 (2023)
3. Casser, V., Pirk, S., Mahjourian, R., et al.: Unsupervised monocular depth and ego-motion learning with structure and semantics. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)
4. Chen, Z., Duan, Y., Wang, W., et al.: Vision transformer adapter for dense predictions. In: The Eleventh International Conference on Learning Representations (2022)
5. Choi, H., Lee, H., Kim, S., et al.: Adaptive confidence thresholding for monocular depth estimation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 12808–12818 (2021)