Publisher
Springer Nature Switzerland
Reference55 articles.
1. Badrinarayanan, V., Kendall, A., Cipolla, R.: SegNet: a deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(12), 2481–2495 (2017)
2. Cao, J., Leng, H., Lischinski, D., Cohen-Or, D., Tu, C., Li, Y.: ShapeConv: shape-aware convolutional layer for indoor RGB-D semantic segmentation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 7088–7097 (2021)
3. Chaurasia, A., Culurciello, E.: LinkNet: exploiting encoder representations for efficient semantic segmentation. In: 2017 IEEE Visual Communications and Image Processing (VCIP), pp. 1–4. IEEE (2017)
4. Chen, C., Wei, J., Peng, C., Zhang, W., Qin, H.: Improved saliency detection in RGB-D images using two-phase depth estimation and selective deep fusion. IEEE Trans. Image Process. 29, 4296–4307 (2020)
5. Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Semantic image segmentation with deep convolutional nets and fully connected CRFs. arXiv preprint arXiv:1412.7062 (2014)
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献