[46] Xinyi Liu, Qi Xie, Qian Zhao, Hong Wang and Deyu Meng. Low-light image enhancement by Retinex-based algorithm unrolling and adjustment. Accepted by IEEE Transactions on Neural Networks and Learning Systems, 2023.

[45] Hong Wang, Qi Xie, Qian Zhao, Yuexiang Li, Yong Liang, Yefeng Zheng and Deyu Meng. RCDNet: An interpretable rain convolutional dictionary network for single image deraining. Accepted by IEEE Transactions on Neural Networks and Learning Systems, 2023.

[44] Qian Zhao, Yuji Lin, Fengxingyu Wang and Deyu Meng. Adaptive weighting function for weighted nuclear norm based matrix/tensor completion. International Journal of Machine Learning and Cybernetics, 15(2):697-718, 2024.

[43] Zhengyang Hu, Jiang Xue, Feng Li, Qian Zhao, Deyu Meng and Zongben Xu. Robust channel estimation based on the maximum entropy principle. Science China Information Sciences, 66(12):222304(13), 2023.

[42] Zina Li, Yao Wang, Qian Zhao, Shijun Zhang and Deyu Meng. A tensor-based online RPCA model for compressive background subtraction. IEEE Transactions on Neural Networks and Learning Systems, 34(12):10668-10682, 2023.

[41] Qian Zhao, Hui Wang, Xuehu Zhu and Deyu Meng. Stein variational gradient descent with learned direction. Information Sciences, 637:118975(11), 2023.

[40] Qi Xie, Qian Zhao, Zongben Xu and Deyu Meng. Fourier series expansion based filter parametrization for equivariant convolutions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4):4537-4551, 2023.

[39] Jun Shu, Yanwen Zhu, Qian Zhao, Deyu Meng and Zongben Xu. MLR-SNet: Transferable LR schedules for heterogeneous tasks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3):3505-3521, 2023.

[38] Qian Zhao, Jun Shu, Xiang Yuan, Ziming Liu and Deyu Meng. A probabilistic formulation for meta-weight-net. IEEE Transactions on Neural Networks and Learning Systems, 34(3):1194-1208, 2023.

[37] Qian Zhao*, Hui Wang*, Zongsheng Yue and Deyu Meng. A deep variational Bayesian framework for blind image deblurring. Knowledge-Based Systems, 249:109008(14), 2022. (*Contributed equally)

[36] Qi Xie, Minghao Zhou, Qian Zhao, Zongben Xu and Deyu Meng. MHF-Net: An interpretable deep network for multispectral and hyperspectral image fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(3):1457-1473, 2022.

[36] Heng Du, Yun Deng, Jiang Xue, Deyu Meng, Qian Zhao and Zongben Xu. Robust online CSI estimation in a complex environment. IEEE Transactions on Wireless Communications, 21(10): 8322-8336, 2022.

[35] Hong Wang, Yichen Wu, Minghan Li, Qian Zhao and Deyu Meng. Survey on rain removal from videos or a single image. SCIENCE CHINA Information Sciences, 65(1):092115(14), 2022.

[34] Junmin Liu, Shuai Yuan, Xuehu Zhu, Yifan Huang and Qian Zhao. Nonnegative matrix factorization with entropy regularization for hyperspectral unmixing. International Journal of Remote Sensing, 42(16):6359-6390, 2021.

[33] Lixuan Yi, Qian Zhao, Wei Wei and Zongben Xu. Robust online rain removal for surveillance videos with dynamic rains. Knowledge-Based Systems, 222:107006(17), 2021.

[32] Kaidong Wang, Yao Wang, Qian Zhao, Deyu Meng, Xiuwu Liao and Zongben Xu. SPLBoost: an improved robust boosting algorithm based on self-paced learning. IEEE Transactions on Cybernetics, 51(3):1556-1570, 2021.

[31] Minghan Li, Xiangyong Cao, Qian Zhao, Lei Zhang and Deyu Meng. Online rain/snow removal from surveillance videos. IEEE Transactions on Image Processing, 30:2029-2044, 2021.

[30] Junxiong Jia, Qian Zhao, Zongben Xu, Deyu Meng and Yee Leung. Variational Bayes' method for functions with applications to some inverse problems. SIAM Journal on Scientific Computing, 43(1):A355-A383, 2021. 

[29] Hong Wang, Yichen Wu, Qi Xie, Qian Zhao, Yong Liang, Shijun Zhang and Deyu Meng. Structural residual learning for single image rain removal. Knowledge-Based Systems, 213:106595(12), 2021.

[28] Qi Xie, Qian Zhao, Zongben Xu and Deyu Meng. Color and direction-invariant nonlocal self-similarity prior and its application to color image denoising. SCIENCE CHINA Information Sciences, 63:222101(17), 2020.

[27] Yuanke Zhang, Jiangjun Peng, Dong Zeng, Qi Xie, Sui Li, Zhaoying Bian, Yongbo Wang, Yong Zhang, Qian Zhao, Hao Zhang, Zhengrong Liang, Hongbing Lu, Deyu Meng and Jianhua Ma. Contrast-medium anisotropy-aware tensor total variation model for robust cerebral perfusion CT reconstruction with low-dose scans. IEEE Transactions on Computational Imaging, 6:1375-1388, 2020.

[26] Jiangjun Peng*, Qi Xie*, Qian Zhao, Yao Wang, Yee Leung and Deyu Meng. Enhanced 3DTV regularization and its applications on HSI denoising and compressed sensing. IEEE Transactions on Image Processing, 29:7889-7903, 2020.  (*Contributed equally)

[25] Dong Zeng, Lisha Yao, Yongshuai Ge, Sui Li, Qi Xie, Hao Zhang, Zhaoying Bian, Qian Zhao, Yuanqing Li, Zongben Xu, Deyu Meng and Jianhua Ma. Full-spectrum-knowledge-aware tensor model for energy-resolved CT iterative reconstruction. IEEE Transactions on Medical Imaging, 39(9):2831-2843, 2020.

[24] Hong Wang, Qi Xie, Yichen Wu, Qian Zhao and Deyu Meng. Single image rain streaks removal: a review and an exploration. International Journal of Machine Learning and Cybernetics, 11:853-872, 2020.

[23] Qian Zhao, Xiangyu Rui, Zhi Han and Deyu Meng. Multilinear multitask learning by rank-product regularization. IEEE Transactions on Neural Networks and Learning Systems, 31(4):1336-1350, 2020.

[22] Zongsheng Yue, Hongwei Yong, Deyu Meng, Qian Zhao, Yee Leung and Lei Zhang. Robust multi-view subspace learning with non-independently and non-identically distributed complex noise. IEEE Transactions on Neural Networks and Learning Systems, 31(4):1070-1083, 2020.

[21] Jing Yao, Deyu Meng, Qian Zhao, Wenfei Cao and Zongben Xu. Nonconvex-sparsity and nonlocal-smoothness based blind hyperspectral unmixing. IEEE Transactions on Image Processing, 28(6):2991-3006, 2019. 

[20] Xi’ai Chen, Zhi Han, Yao Wang, Qian Zhao, Deyu Meng, Lin Lin and Yandong Tang. A generalized model for robust tensor factorization with noise modeling by mixture of Gaussians. IEEE Transactions on Neural Networks and Learning Systems, 29(11):5380-5393, 2018.

[19] Zongsheng Yue, Deyu Meng, Yongqing Sun and Qian Zhao. Hyperspectral image restoration under complex multi-band noises. Remote Sensing, 10(10):1631, 2018.

[18] Qi Xie, Qian Zhao, Deyu Meng and Zongben Xu. Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(8):1888-1902, 2018.

[17] Chenqiang Gao, Lan Wang, Yongxing Xiao, Qian Zhao and Deyu Meng. Infrared small-dim target detection based on Markov random field guided noise modeling. Pattern Recognition, 76:463-475, 2018.

[16] Yao Wang, Jiangjun Peng, Qian Zhao, Deyu Meng, Yee Leung and Xi-Le Zhao. Hyperspectral image restoration via total variation regularized low-rank tensor decomposition. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(4):1227-1243, 2018.

[15] Yang Chen, Xiangyong Cao, Qian Zhao, Deyu Meng and Zongben Xu. Denoising hyperspectral image with non-i.i.d. noise structure. IEEE Transactions on Cybernetics, 48(3):1054-1066, 2018.

[14] Jing Yao*, Xiangyong Cao*, Qian Zhao, Deyu Meng and Zongben Xu. Robust subspace clustering via penalized mixture of Gaussians. Neurocomputing, 278:4-11, 2018.  (*Contributed equally)

[13] Yao Wang, Lin Lin, Qian Zhao, Tianwei Yue, Deyu Meng and Yee Leung. Compressive Sensing of Hyperspectral Images via Joint Tensor Tucker Decomposition and Weighted Total Variation regularization. IEEE Geoscience and Remote Sensing Letters, 14(12):2457-2461, 2017.

[12] Qi Xie, Dong Zeng, Qian Zhao, Jianhua Ma, Zongben Xu, Zhenrong Liang and Deyu Meng. Robust low-dose CT sinogram prepocessing via exploiting noise-generating mechanism. IEEE Transactions on Medical Imaging, 36(12):2487-2498, 2017.

[11] Deyu Meng, Qian Zhao and Lu Jiang. A theoretical understanding of self-paced learning. Information Sciences, 414:319-328, 2017.

[10] Xiangyong Cao, Lin Xu, Deyu Meng, Qian Zhao and Zongben Xu. Integration of 3-dimensional discrete wavelet transform and Markov random field for hyperspectral image classification. Neurocomputing, 226:90-100, 2017.

[9]   Xiangyong Cao, Qian Zhao, Deyu Meng, Yang Chen and Zongben Xu. Robust low-rank matrix factorization under general mixture noise distributions. IEEE Transactions on Image Processing, 25(10):4677-4690, 2016.

[8]   Lingling Wang, Qian Zhao, Jinghuai Gao, Zongben Xu, Michael Fehler and Xiudi Jiang. Seismic sparse-spike deconvolution via Toeplitz-sparse matrix factorization. Geophysics, 81(2):169-182, 2016.

[7]   Tieliang Gong, Qian Zhao, Deyu Meng and Zongben Xu. Why curriculum learning & self-paced learning work in big/noisy data: a theoretical perspective. Big Data and Information Analytics, 1(1):111-127, 2016.

[6]   Qian Zhao, Deyu Meng, Zongben Xu, Wangmeng Zuo and Yan Yan. L1-norm low-rank matrix factorization by variational Bayesian method. IEEE Transactions on Neural Networks and Learning Systems, 26(4):825-839, 2015.

[5]   Qian Zhao, Deyu Meng, Zongben Xu and Chenqiang Gao. A block coordinate descent approach for sparse principal component analysis. Neurocomputing, 153:180-190, 2015.

[4]   Qian Zhao, Deyu Meng and Zongben Xu. Robust sparse principal component analysis. SCIENCE CHINA Information Sciences, 57:092115(14), 2014.

[3]   Deyu Meng, Qian Zhao, Yee Leung and Zongben Xu. Learning dictionary from signals under global sparsity constraint. Neurocomputing, 119:308-318, 2013.

[2]   Deyu Meng, Qian Zhao and Zongben Xu. Improve robustness of sparse PCA by L1-norm maximization. Pattern Recognition, 45(1):487-497, 2012.

[1]   Qian Zhao, Deyu Meng and Zongben Xu. L1/2 regularized logistic regression. Pattern Recognition and Artifical Intelligence (In Chinese), 25(5):721-728, 2012.

[26] Jiangtao Zhang, Zongsheng Yue, Hui Wang, Qian Zhao and Deyu Meng. Blind image deconvolution by generative-based kernel prior and initializer via latent encoding. In: Proceedings of the 18th European  Conference on Computer Vision (ECCV), Milan, Italy, 2024.

[25] Minghao Zhou, Hong Wang, Qian Zhao, Yuexiang Li, Yawen Huang, Deyu Meng and Yefeng Zheng. Interactive segmentation as Gaussian process classification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, 2023.

[24] Jiahong Fu, Hong Wang, Qi Xie, Qian Zhao, Deyu Meng and Zongben Xu. KXNet: A model-driven deep neural network for blind super-resolution. In: Proceedings of the 17th European  Conference on Computer Vision (ECCV), Tel Aviv, Israel, 2022.

[23] Zongsheng Yue, Qian Zhao, Jianwen Xie, Lei Zhang, Deyu Meng and Kwan-Yee K Wong. Blind image super-resolution with elaborate degradation modeling on noise and kernel. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, USA, 2022.

[22] Zongsheng Yue, Jianwen Xie, Qian Zhao and Deyu Meng. Semi-supervised video deraining with dynamical rain generator. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online, 2021.

[21] Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng and Deyu Meng. From rain generation to rain removal. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online, 2021.

[20] Xiangyu Rui, Xiangyong Cao, Qi Xie, Zongsheng Yue, Qian Zhao and Deyu Meng. Learning an explicit weighting scheme for adapting complex HSI noise. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online, 2021.

[19] Yichen Wu, Jun Shu, Qi Xie, Qian Zhao and Deyu Meng. Learning to purify noisy labels via meta soft label corrector. In: Proceedings of  the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), Online, 2021.

[18] Zongsheng Yue, Qian Zhao, Lei Zhang and Deyu Meng. Dual adversarial network: Toward real noise removal and noise generation. In: Proceedings of the 16th European  Conference on Computer Vision (ECCV), Online, 2020.

[17] Hong Wang, Qi Xie, Qian Zhao and Deyu Meng. A model-driven deep neural network for single image rain removal. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online, 2020.

[16] Zhengyang Hu, Jiang Xue, Deyu Meng, Qian Zhao and Zongben Xu. MEP-Based channel estimation under complex communication environment. In: Proceedings of the IEEE International Conference on Communications (ICC), Online, 2020.

[15] Jun Shu, Qi Xie, Lixuan Yi, Qian Zhao, Sanping Zhou, Zongben Xu and Deyu Meng. Meta-weight-net: learning an explicit mapping for sample weighting. In: Advances in Neural Information Processing Systems 32 (NeurIPS), Vancouver, Canada, 2019.

[14] Zongsheng Yue, Hongwei Yong, Qian Zhao, Lei Zhang and Deyu Meng. Variational denoising network: toward blind noise modeling and removal. In: Advances in Neural Information Processing Systems 32 (NeurIPS), Vancouver, Canada, 2019.

[13] Qi Xie, Minghao Zhou, Qian Zhao, Deyu Meng, Wangmeng Zuo and Zongben Xu. Multispectral and hyperspectral image fusion by MS/HS fusion net. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019.

[12] Wei Wei, Deyu Meng, Qian Zhao, Zongben Xu and Ying Wu. Semi-supervised transfer learning for image rain removal. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019. 

[11] Haipei Zhang, Jiang Xue, Deyu Meng, Qian Zhao and Zongben Xu. Robust CSI estimation under complex communication environment. In: Proceedings of the IEEE International Conference on Communications (ICC), Shanghai, China, 2019.

[10] Minghan Li, Qi Xie, Qian Zhao, Wei Wei, Shuhang Gu, Jing Tao and Deyu Meng. Video rain streak removal by multiscale convolutional sparse coding. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, 2018.

[9]   Wei Wei, Lixuan Yi, Qi Xie, Qian Zhao, Deyu Meng and Zongben Xu. Should we encode rain streaks in video as deterministic or stochastic? In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 2017.

[8]   Qi Xie, Qian Zhao, Deyu Meng, Zongben Xu, Shuhang Gu, Wangmeng Zuo and Lei Zhang. Multispectral images denoising by intrinsic tensor sparsity regularization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, 2016.

[7]   Xi’ai Chen, Zhi Han, Yao Wang, Qian Zhao, Deyu Meng and Yandong Tang. Robust tensor factorization with unknown noise. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, 2016.

[6]   Qian Zhao, Deyu Meng, Xu Kong, Qi Xie, Wenfei Cao, Yao Wang and Zongben Xu. A novel sparsity measure for tensor recovery. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.

[5]   Xiangyong Cao, Yang Chen, Qian Zhao, Deyu Meng, Yao Wang, Dong Wang and Zongben Xu. Low-rank matrix factorization under general mixture noise distributions. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.

[4]   Dingwen Zhang, Deyu Meng, Chao Li, Lu Jiang, Qian Zhao and Junwei Han. A self-paced multiple-instance learning framework for co-saliency detection. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.

[3]   Qian Zhao, Deyu Meng, Lu Jiang, Qi Xie, Zongben Xu and Alexander Hauptmann. Self-paced learning for matrix factorization. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), Austin, USA, 2015.

[2]   Lu Jiang, Deyu Meng, Qian Zhao, Shiguang Shan and Alexander Hauptmann. Self-paced curriculum learning. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), Austin, USA, 2015.

[1]   Qian Zhao, Deyu Meng, Zongben Xu, Wangmeng Zuo and Lei Zhang. Robust principal component analysis with complex noise. In: Proceedings of the 31st International Conference on Machine Learning (ICML), Beijing, China, 2014.