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Articles

PCNet: partial convolution attention mechanism for image inpainting

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Pages 738-745 | Received 15 Dec 2019, Accepted 21 Mar 2021, Published online: 15 Apr 2021

References

  • Barnes C, Shechtman E, Finkelstein A, et al. Patchmatch: A randomized correspondence algorithm for structural image editing. ACM Trans Graph. 2009;28(3):1–11.
  • Bertalmio M, Sapiro G, Caselles V, et al. Image inpainting. Proceedings of the 27th annual conference on computer graphics and interactive techniques. ACM Press/Addison-Wesley Publishing Co.; 2000. p. 417–424.
  • Efros AA, Freeman WT. Image quilting for texture synthesis and transfer. Proceedings of the 28th annual conference on Computer graphics and interactive techniques. ACM; 2001. p. 341–346.
  • Efros AA, Leung TK. Texture synthesis by non-parametric sampling: Proceedings of the seventh IEEE international conference on computer vision. IEEE. 1999;2:1033–1038.
  • Huang Z, Wang X, Huang L, et al. Ccnet: Criss-cross attention for semantic segmentation. Proceedings of the IEEE International Conference on Computer Vision; 2019. p. 603–612.
  • Ballester C, Bertalmio M, Caselles V, et al. Filling-in by joint interpolation of vector fields and gray levels. IEEE Trans Image Process. 2001;10(8):1200–1211.
  • Brown JR. Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques. ACM Press/Addison-Wesley Publishing Company; 2000.
  • Liu D, Sun X, Wu F, et al. Image compression with edge-based inpainting. IEEE Trans Circuits Syst Video Technol. 2007;17(10):1273–1287.
  • Florinabel D J, Juliet S E, Sadasivam V. Fast orientation driven multi-structure morphological inpainting, Digital Photography VII. International Society for Optics and Photonics; 2011, 7876: 78760E.
  • Criminisi A, P'erez P, Toyama Region K. Filling and object removal by exemplar-based image inpainting. IEEE Trans Image Process. 2004;13(9):1200–1212.
  • Darabi S, Shechtman E, Barnes C, et al. Image melding: combining inconsistent images using patch-based synthesis. ACM Trans Graph; 2012; 31(4): 1–10
  • Drori I, Cohen-Or D, Yeshurun H. Fragment-based image completion. ACM Trans Graph. 2003;22(3):303–312.
  • Huang J B, Kang S B, Ahuja N, et al. Image completion using planar structure guidance. ACM Trans Graph. 2014;33(4):1–10.
  • Hung K M, Chen Y L, Hsieh C T. Image inpainting based on geometric similarity. Int J Comput Appl. 2012;34(1):11–18.
  • Guillemot C, Le Meur O. Image inpainting: Overview and recent advances. IEEE Signal Process. Mag. 2014;31(1):127–144.
  • Pathak D, Krahenbuhl P, Donahue J, et al. Context encoders: feature learning by inpainting. Proceedings of the IEEE conference on computer vision and pattern recognition; 2016. p. 2536–2544.
  • Iizuka S, Simo-Serra E, Ishikawa H. Globally and locally consistent image completion. ACM Trans Graph. 2017;36(4CD):107.1–107.14.
  • Yu J, Lin Z, Yang J, et al. Generative image inpainting with contextual attention. Proceedings of the IEEE conference on computer vision and pattern recognition; 2018. p. 5505–5514.
  • Liu G, Reda F A, Shih K J, et al. Image inpainting for irregular holes using partial convolutions. Proceedings of the European conference on computer vision; 2018. p. 85–100.
  • Nazeri K, Ng E, Joseph T, et al. Edgeconnect: Generative image inpainting with adversarial edge learning. arXiv preprint arXiv:1901.00212; 2019.
  • Zheng C, Cham T J, Cai J. Pluralistic image completion. Proceedings of the IEEE conference on computer vision and pattern recognition; 2019. p. 1438–1447.
  • Ma Y, Liu X, Bai S, et al. Coarse-to-fine image inpainting via region-wise convolutions and non-local correlation. Proceedings of the 28th International Joint Conference on Artificial Intelligence. AAAI Press; 2019. p. 3123–3129.
  • Guo Z, Chen Z, Yu T, et al. Progressive image inpainting with full-resolution residual network. Proceedings of the 27th ACM International Conference on Multimedia. ACM; 2019. p. 2496–2504.
  • Liu H, Jiang B, Song Y, et al. Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations. arXiv preprint arXiv:2007.06929; 2020.
  • Hu J, Shen L, Sun G. Squeeze-and-excitation networks. Proceedings of the IEEE conference on computer vision and pattern recognition; 2018. p. 7132–7141.
  • Zhang H, Goodfellow I, Metaxas D, et al. Self-attention generative adversarial networks. arXiv preprint arXiv:1805.08318; 2018.
  • Wang X, Girshick R, Gupta A, et al. Non-local neural networks. Proceedings of the IEEE conference on computer vision and pattern recognition; 2018. p. 7794–7803.
  • Li X, Sun W, Wu T. Attentive Normalization. arXiv preprint arXiv:1908.01259; 2019.

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