Semantic Edge Detection with Diverse Deep Supervision-Reference-Cited by-同舟云学术

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Semantic Edge Detection with Diverse Deep Supervision

Published:2021-11-29 Issue:1 Volume:130 Page:179-198
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vis

Author:

Liu Yun,Cheng Ming-Ming^ORCID,Fan Deng-Ping,Zhang Le,Bian Jia-Wang,Tao Dacheng

Funder

NSFC

The national youth talent support program

Tianjin Natural Science Foundation

Major Project for New Generation of AI

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s11263-021-01539-8.pdf

Reference65 articles.

1. Acuna, D., Kar, A., & Fidler, S. (2019). Devil is in the edges: Learning semantic boundaries from noisy annotations. In IEEE conference on computer vision and pattern recognition (pp. 11075–11083).

2. Amer, M. R., Yousefi, S., Raich, R., & Todorovic, S. (2015). Monocular extraction of 2.1D sketch using constrained convex optimization. International Journal of Computer Vision, 112(1), 23–42.

3. Arbeláez, P., Maire, M., Fowlkes, C., & Malik, J. (2011). Contour detection and hierarchical image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(5), 898–916.

4. Bertasius, G., Shi, J., & Torresani, L. (2015a). DeepEdge: A multi-scale bifurcated deep network for top-down contour detection. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4380–4389).

5. Bertasius, G., Shi, J., & Torresani, L. (2015b). High-for-low and low-for-high: Efficient boundary detection from deep object features and its applications to high-level vision. In Proceedings of the IEEE international conference on computer vision (pp. 504–512).

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