[1] Gatys L A, Ecker A S, Bethge M. Image style transfer using convolutional neural networks. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2414-2423(2016).
[2] Johnson J, Alahi A, Li F F. Perceptual losses for real-time style transfer and super-resolution. [C]∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 694-711(2016).
[3] Yanai K, Tanno R. Conditional fast style transfer network. [C]∥Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval, June 6-9, 2017, Bucharest, Romania. New York: ACM, 434-437(2017).
[4] Li Y, Fang C, Yang J et al. Universal style transfer via feature transforms. [C]∥Advances in Neural Information Processing Systems, December 4-9, 2017, Long Beach, CA, USA. San Diego: NIPS, 386-396(2017).
[5] Iizuka S, Simo-Serra E, Ishikawa H. Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification[J]. ACM Transactions on Graphics (TOG), 35, 110(2016).
[8] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).
[9] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 3431-3440(2016).
[10] Zhou L L, Jiang F. Survey on image segmentation methods[J]. Application Research of Computers, 34, 1921-1928(2017).
[13] Li M J. Logic operation in arithmetic[J]. Journal of Electrical & Electronic Education, 39, 115-117(2017).
[14] Simonyan K. -04-10)[2019-07-29]. https:∥arxiv.xilesou., top/abs/1409, 1556(2015).
[15] Zhang K, Sun M, Han T X et al. Residual networks of residual networks: multilevel residual networks[J]. IEEE Transactions on Circuits and Systems for Video Technology, 28, 1303-1314(2018).
[16] Han D, Kim J, Kim J. Deep pyramidal residual networks. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 5927-5935(2016).
[17] Shen F L, Gan R, Zeng G. Weighted residuals for very deep networks. [C]∥The 2016 3rd International Conference on Systems and Informatics (ICSAI), November 19-21, 2016, Shanghai, China. New York: IEEE, 936-941(2017).
[18] Chetlur S, Woolley C, Vandermersch P et al. -12-18)[2019-07-29]. https:∥arxiv.xilesou., top/abs/1410, 0759(2014).
[19] Lin T Y, Maire M, Belongie S et al. Microsoft COCO: common objects in context. [C]∥Fleet D, Pajdla T, Schiele B, et al. Computer vision-ECCV 2014. Lecture notes in computer science. Cham: Springer, 740-755(2014).
[20] Kingma D P. -01-30)[2019-07-29]. https:∥arxiv.xilesou., top/abs/1412, 6980(2017).
[21] Zhang H, Dana K. Multi-style generative network for real-time transfer. [C]∥Proceedings of the European Conference on Computer Vision (ECCV), September 8-14, 2018, Munich, Germany. New York: IEEE(2018).