跳至正文

历年论文

2022

  • T. Wang, F. Fang, H. Zheng, and G. Zhang, “Frmlnet: Framelet-based multilevel network for pansharpening,” IEEE Transactions on Cybernetics, 2022.
  • Q. Yi, J. Li, F. Fang, A. Jiang, and G. Zhang, “Efficient and accurate multi-scale topological network for single image dehazing,” IEEE Transactions on Multimedia, 2022.
  • P. Lu, F. Fang, H. Zhang, L. Ling, and K. Hua, “Augms-net: Augmented multiscale network for small cervical tumor segmentation from mri volumes,” Computers in Biology and Medicine, vol. 141, p. 104774, 2022.
  • Y. Ru, F. Li, F. Fang, and G. Zhang, “Patch-based weighted scad prior for compressive sensing,” Information Sciences, vol. 592, pp. 137–155, 2022.

2021

  • Y. Liu, F. Fang , T. Wang, J. Li , Y. Sheng, and G. Zhang, Multi-Scale Grid Network for Image Deblurring With High-Frequency Guidance, *IEEE Transactions on Multimedia (TMM)*,2021. (SCI一区)
  • Y. Yuan, F. Fang, and G. Zhang, “Super pixel based Seamless Image Stitching for UAV Images,” IEEE Transactions on Geoscience and Remote Sensing (TGRS),59(2): 1565-1576, 2021.
  • Q. Dai, F. Fang, J. Li, G. Zhang, and A. Zhou, “Edge-guided composition network for image stitching,” Pattern Recognition, vol. 118, p. 108019, 2021.
  • Q. Dai, J. Li, Q. Yi, F. Fang, and G. Zhang, “Feedback network for mutually boosted stereo image super-resolution and disparity estimation,” in Proceedings of the 29th ACM International Conference on Multimedia, 2021, pp. 1985–1993.
  • Q. Yi, J. Li, Q. Dai, F. Fang, G. Zhang, and T. Zeng, “Structure-preserving deraining with residue channel prior guidance,” in Proceedings of the IEEE/CVF International Conference on Computer Vision(ICCV), 2021, pp. 4238–4247.
  • L. Chen, J. Zhang, S. Lin, F. Fang, and J. S. Ren, “Blind deblurring for saturated images,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), 2021, pp. 6308–6316.
  • L. Chen, J. Zhang, J. Pan, S. Lin, F. Fang, and J. S. Ren, “Learning a non-blind deblurring network for night blurry images,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), 2021, pp.10 542–10 550.

2020

  • J. Li, J. Li, F. Fang, F. Li, and G. Zhang, “Luminance-aware pyramid network for low-light image enhancement,” IEEE Transactions on Multimedia, vol. 23, pp. 3153–3165, 2020.(SCI一区)
  • S. Zhou, W. Zhang, C. Shen, Rate-distortion model for grayscale-invariance reversible data hiding, Signal Processing, 172, 2020, 107562
  • F. Fang, J. Li, Y. Yuan, T. Zeng, and G. Zhang, “Multilevel edge features guided network for image denoising,” IEEE Transactions on Neural Networks and Systems, Learning, vol. 32, no. 9, pp. 3956–3970, 2020. (SCI一区)
  • F. Fang, J. Li, and T. Zeng, “Soft-edge assisted network for single image super resolution,” IEEE Transactions on Image Processing, vol. 29, pp. 4656–4668,2020.
  • F. Fang, T. Wang, Y. Wang, T. Zeng, and G. Zhang, “Variational single image dehazing for enhanced visualization,” IEEE Transactions on Multimedia, vol. 22,no. 10, pp. 2537–2550, 2020.
  • F. Fang, T. Wang, S. Wu, and G. Zhang, “Removing moire patterns from single images,” Information Sciences, vol. 514, pp. 56–70, 2020. (SCI一区)
  • F. Fang, T. Wang, T. Zeng, and G. Zhang, “A super pixel-based variational model for image colorization,” IEEE Transactions on Visualization and Graphics, Computer, vol. 26, no. 10, pp. 2931–2943, 2020.
  • Z. Xu, T. Wang, F. Fang, Y. Sheng, and G. Zhang, “Stylization-based architecture for fast deep exemplar colorization,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), 2020, pp. 9363–9372.
  • L. Chen, F. Fang, J. Zhang, J. Liu, and G. Zhang, “Oid: Outlier identifying and discarding in blind image deblurring,” in The European Conference on Computer Vision (ECCV). Springer, 2020, pp. 598–613.
  • L. Chen, F. Fang, S. Lei, F. Li, and G. Zhang, “Enhanced sparse model for blind deblurring,” in The European Conference on Computer Vision (ECCV).Springer, 2020, pp. 631–646.
  • J. Li, F. Fang, J. Li, K. Mei, and G. Zhang, “Mdcn: Multi-scale dense cross network for image super-resolution,” IEEE Transactions on Circuits and Technology, Systems for Video, vol. 31, no. 7, pp. 2547–2561, 2020.
  • Z. Gu, F. Li, F. Fang, and G. Zhang, “A novel retinex-based fractional-order variational model for images with severely low light,” IEEE Transactions on Image Processing, vol. 29, pp. 3239–3253, 2020.

2019

  • Chenxiao Zhao, P. Thomas Fletcher, Mixue Yu, Yaxin Peng, Guixu Zhang, Chaomin Shen: The adversarial attack and detection under the Fisher information metric. AAAI 2019: 5869-5876
  • H. Zheng, F. Fang, and G. Zhang, “Cascaded dilated dense network with twostep data consistency for mri reconstruction,” Advances in Neural Information Processing Systems, vol. 32, 2019.
  • L. Chen, F. Fang, T. Wang, and G. Zhang, “Blind image deblurring with local maximum gradient prior,” in IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2019, pp. 1742–1750.
  • T. Wang, F. Fang, F. Li, and G. Zhang, “High-quality bayesian pansharpening,” IEEE Transactions on Image Processing, vol. 28, no. 1, pp. 227–239, 2019.
  • F. Fang, T. Wang, Y. Fang, and G. Zhang, “Fast color blending for seamless image stitching,” IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 7, pp. 1115–1119, 2019.
  • H. Chen and F. Fang, “Bregman-tanimoto based method for contrast preserving decolorization,” in IEEE International Conference on Multimedia and Expo(ICME). IEEE, 2019, pp. 1240–1245.

2018

  • J. Li, F. Fang, K. Mei, and G. Zhang, “Multi-scale residual network for image super-resolution,” in Proceedings of the European conference on computer vision(ECCV), 2018, pp. 517–532.

2017

  • F. Fang, F. Li, and T. Zeng, “Reducing spatially varying out-of-focus blur from natural image,” Inverse Problems and Imaging, vol. 11, no. 1, pp. 65–85, 2017.

2016

  • G. Zhang, Y. Xu, and F. Fang, “Framelet-based sparse unmixing of hyperspectral images,” IEEE Transactions on Image Processing, vol. 25, no. 4, pp. 1516–1529,2016.

2014

  • F. Fang, F. Li, and T. Zeng, “Single image dehazing and denoising: A fast variational approach,” SIAM Journal on Imaging Sciences, vol. 7, no. 2, pp. 969–996, 2014.
  • C. Li, F. Fang, A. Zhou, and G. Zhang, “A novel blind spectral unmixing method based on error analysis of linear mixture model,” IEEE geoscience and remote sensing letters, vol. 11, no. 7, pp. 1180–1184, 2014.

2013

  • F. Fang, F. Li, C. Shen, and G. Zhang, “A variational approach for pan-sharpening,” IEEE Transactions on Image Processing, vol. 22, no. 7, pp. 2822–2834, 2013.