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Bokeh effect is a natural shallow depth-of-field phenomenon that blurs the out-of-focus part in photography.
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2020
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A. S. Shamsabadi, R. Sanchez-Matilla, and A. Cavallaro, “Colorfool: Semantic adversarial colorization,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 1151–1160
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2020
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2020
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A. Abuolaim, M. Delbracio, D. Kelly, M. S. Brown, and P. Milanfar, “Learning to reduce defocus blur by realistically modeling dual-pixel data,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 2289–2298
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2022
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Z. Wang, A. Jiang, C. Zhang, H. Li, and B. Liu, “Self-supervised multi-scale pyramid fusion networks for realistic bokeh effect rendering,” Journal of Visual Communication and Image Representation , vol. 87, p. 103580, 2022
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H. Nagasubramaniam and R. Younes, “Bokeh effect rendering with vision transformers,” 2022
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S. Zhang, D. Zuo, Y. Yang, and X. Zhang, “A transferable adversarial belief attack with salient region perturbation restriction,” IEEE Transactions on Multimedia , 2022
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Q. Meng, S. Zhang, Z. Li, C. Wang, W. Zhang, and Q. Huang, “Automatic shadow generation via exposure fusion,” IEEE Transactions on Multimedia , 2023
2023
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T. Seizinger, M. V. Conde, M. Kolmet, T. E. Bishop, and R. Timofte, “Efficient multi-lens bokeh effect rendering and transformation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 1633–1642
2023
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Z. Yang, W. Lian, and S. Lai, “Bokehornot: Transforming bokeh effect with image transformer and lens metadata embedding,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 1542–1550
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