“Image Processing GNN: Breaking Rigidity in Super-Resolution,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 24108–24117. [Martin+ 2002] D. Martin, C. Fowlkes, D. Tal, and J. Malik, “A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics,” in Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, IEEE Comput. Soc, 2002. doi: 10.1109/iccv.2001.937655. [Wang+ 2004] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process., vol. 13, no. 4, pp. 600–612, Apr. 2004. [Bevilacqua+ 2012] M. Bevilacqua, A. Roumy, C. Guillemot, and M. L. Alberi-Morel, “Low-complexity single-image super-resolution based on nonnegative neighbor embedding,” in Proceedings of the 23rd British Machine Vision Conference (BMVC), BMVA Press, 2012, p. 135.1-135.10. [Zeyde+ 2012] R. Zeyde, M. Elad, and M. Protter, “On single image scale-up using sparse-representations,” in Curves and Surfaces, in Lecture notes in computer science. , Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 711–730. [Goodfellow+ 2014] I. Goodfellow et al., “Generative Adversarial Nets,” in Advances in Neural Information Processing Systems, Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, and K. Q. Weinberger, Eds., Curran Associates, Inc., 2014. [Online]. Available: https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf 参考⽂献