Qian Ning

Happy and Healthy

Qian Ning

I am currently pursuing the Ph.D degree in Xidian University, China. My supervisor is Weisheng Dong. Before that I received my B.E degree from School of Electronic Engineering, Xidian University, China, in Jul. 2019.

My research interest broadly includes deep learning and image/video restoration (e.g., super-resolution, denoising, deblurring, dehazing), face generation and enhancement, and image generation (e.g., GAN prior/inversion).

Publications

  1. Qian Ning, Fangfang Wu, Weisheng Dong, Xin Li, Guangming Shi, “Exploring Correlations in Degraded Spatial Identity Features for Blind Face Restoration,” ACMMM, 2023
  2. Chengxing Xie*, Qian Ning*, Weisheng Dong and Guangming Shi, “TFRGAN: Leveraging Text Information for Blind Face Restoration with Extreme Degradation,” CVPRW,2023. (Equal Contribution)
  3. Qian Ning, Weisheng Dong, Xin Li and Jinjina Wu, “Searching Efficient Model-guided Deep Network for Image Denoising,” IEEE Transactions on Image Processing (TIP), vol. 32, pp. 668–681, 2023
  4. Qian Ning, Jingzhu Tang, Fangfang Wu, Weisheng Dong, Xin Li, and Guangming Shi, “Learning degradation uncertainty for unsupervised real-world image super-resolution,” in Proceedings of the International Conference on International Joint Conferences on Artificial Intelligence (IJCAI), 2022
  5. Qian Ning, Weisheng Dong, Xin Li, Jinjian Wu, and Guangming Shi, “Uncertainty-driven loss for single image super-resolution,” Advances in Neural Information Processing Systems (NeurIPS), vol. 34, pp. 16398–16409, 2021
  6. Qian Ning, Weisheng Dong, Guangming Shi, Leida Li, and Xin Li, “Accurate and lightweight image super-resolution with model-guided deep unfolding network,” IEEE Journal of Selected Topics in Signal Processing (JSTSP), vol. 15, no. 2, pp. 240–252, 2020
  7. Qian Ning, Weisheng Dong, Fangfang Wu, Jinjian Wu, Jie Lin, and Guangming Shi, “Spatial-temporal gaussian scale mixture modeling for foreground estimation,” in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 34, no. 07, 2020, pp. 11791–11798
  8. Qian Ning, Fangfang Wu, Weisheng Dong, Jinjian Wu, Jie Lin, and Guangming Guangming Shi and Xin Li, “Robust Dynamic Background Modeling for Foreground Estimation,” in IEEE International Conference on Visual Communications and Image Processing (VCIP), 2022, pp. 1–5

Academic Service

Conference Reviewer: CVPR, ICCV, NeurIPS, ECCV, AAAI, IJCAI, ACMMM, ICLR.
Journal Reviewer: TPAMI, TIP, TMM, TCSVT, JSTSP, PR.

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