An efficient approach for image de-fencing based on conditional generative adversarial network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-022-02215-1.pdf
Reference29 articles.
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2. Farid, M.S., Mahmood, A., Grangetto, M.: Image de-fencing framework with hybrid inpainting algorithm. Signal Image Video Process. 10(7), 1193–1201 (2016)
3. Kumar, V., Mukherjee, J., Mandal, S.K.D.: Image defencing via signal demixing. In: Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing, pp. 1–8 (2016)
4. Khalid, M., Yousaf, M.M., Murtaza, K., Sarwar, S.M.: Image de-fencing using histograms of oriented gradients. Signal Image Video Process. 12(6), 1173–1180 (2018)
5. Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1125–1134 (2017)
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