
奖励荣誉
2026年 国自然青年科学基金项目B类(原国自然“优青”)
2025年 陕西高等学校科学技术研究优秀成果(排名第四)
2024年 陕西省高校优秀青年人才
2024年 广东省自然科学一等奖(排名第三)
2024年 华为火花奖
2023年 陕西省优秀博士论文
2021年 ACM中国优博提名奖
2022年 CCF优秀博士学位论文激励计划
工作经历
2022.02至今 西安交通大学 数学与统计学院 青拔B类副教授
2020.12至2022.02 西安交通大学 数学与统计学院 青秀A类助理教授 (博后导师:孟德宇)
教育经历
2013.09至2020.12 西安交通大学 应用数学(博士) 导师:徐宗本
2017.09至2018.09 普林斯顿大学 统计学(访问学者) 导师:范剑青
2014.07至2014.09 香港理工大学 计算机(访问学生) 导师:张 磊
2009.09至2013.06 西安交通大学 理科数学实验班(本科)
研究方向:机器学习与图像处理的基础方法、图像处理中的基础深度网络模块设计
在研课题:参数化卷积方法及其应用、模型驱动的深度学习方法、等变深度网络设计
欢迎具有良好数学基础、编程基础,有志于从事机器学习、计算机视觉与人工智能领域研究的同学报考硕士/博士研究生。
名额有限,请有报考意向学生尽早通过邮件发送简历联系。
办公室: 数学楼 318
邮箱: xie.qi@mail.xjtu.edu.cn
Google Scholar:https://scholar.google.com/citations?hl=zh-CN&user=2ZqIzTMAAAAJ
对称先验与等变网络体系相关论文:
Xie Qi, Zhao Qian, Xu Zongben, Meng Deyu. Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2023. [code](解决任意角度的等变卷积无法在底层视觉应用的问题,属于算子级研究,是本团队等变卷积研究的奠基论文)
Xie Qi, Fu Jiahong, Xu Zongben, Meng Deyu*. Rotation Equivariant Arbitrary-scale Image Super-Resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2025. [code] (解决可与经典等变卷积兼容的图像隐式神经表示(INR)构造问题,属于算子级研究,是本团队等变INR研究的奠基论文)
Zhao Zhongchen, Xie Qi*, Huang Keyu, Lei Zhang, Deyu Meng, Xu Zhongben. Rotation Equivariant Mamba for Vision Tasks[J]. arXiv preprint arXiv:2603.09138, 2026. (解决可与经典等变卷积兼容的图像Mamba(VMamba)等变化问题,属于算子级研究,是本团队等变VMamba研究的奠基论文)
Fu Jiahong, Xie Qi*, Meng Deyu, Zongben Xu. Vanilla Group Equivariant Vision Transformer[J]. arXiv preprint arXiv:2602.08047, 2026. (解决可与经典等变卷积兼容的图像Transformer(ViT)等变化问题,属于算子级研究,是本团队等变ViT研究的奠基论文)
Zhao Zhongchen, Wang Jixin, Xie Qi*, HuiLin, Deyu Meng, Zongben Xu. Flash EQ-Linear: Accelerating Equivariant Linear Layers via Group-wise Discrete Fourier Transform[J]. arXiv preprint arXiv:2607.21271, 2026. (解决系统等变网络的计算速率问题,使等变网络在保持性能的同时推理速度可即插即用超过原始网络(理论计算量降为3/8),是本团队等变加速算法的奠基论文)
Tan Feiyu, Xie Qi*, Xu Zongben, Deyu Meng. Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration[J]. arXiv preprint arXiv:2605.13744, 2026. (在图像复原问题中,系统阐明数据对称性先验的定义方式,证明对称性先验与等变网络的对应关系,证明等变网络的合理性与必要性,是本团队等变理论的奠基论文)
Jiahong Fu, Xie Qi*, Meng Deyu, Xu Zongben. Rotation Equivariant Proximal Operator for Deep Unfolding Methods in Image Restoration. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2024. (将本团队的等变算子体系应用于近端算子的构造,是本团队等变网络体系应用的典型案例)
模型驱动的可解释网络架构相关论文:
Xie Qi, Zhou Minghao, Zhao Qian, Meng Deyu and Xu Zongben. MHF-Net: An interpretable deep network for multispectral and hyperspectral image fusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2020, 44(3): 1457-1473. ( ESI高被引)
Wang Hong#, Xie Qi#, Zhao Qian and Meng Deyu*. A Model-Driven Deep Neural Network for Single Image Rain Removal [C]. CVPR, 2020
传统模型构造相关论文:
Xie Qi, Zhao Qian, Meng Deyu and Xu Zongben. Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2018, 40(8):1888–1902. (ESI高被引)
Xie Qi, Zeng Dong, Zhao Qian, Meng Deyu, Xu Zongben, Liang Zhengrong and Ma Jianhua. Robust low-dose CT sinogram preprocessing via exploiting noise-generating mechanism[J]. IEEE Transactions on Medical Imaging (TMI). 2017, 36(12):2487–2498.
主要论文发表:
Che Yizhuo, Bush Stephen J., Lin Hui, Li Mingxuan, Yang Xiaofei, Xie Qi, Liu Yuchun, Meng Deyu, Ye Kai. The evolution of high-order genome architecture revealed from 1,000 species[J]. Cell, 2026, 189(12): 3760-3772. e19.
Xie Qi, Fu Jiahong, Xu Zongben, Meng Deyu*. Rotation Equivariant Arbitrary-scale Image Super-Resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2025. [code]
Jiahong Fu, Xie Qi*, Meng Deyu, Xu Zongben. Rotation Equivariant Proximal Operator for Deep Unfolding Methods in Image Restoration. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2024.
Xie Qi, Zhao Qian, Xu Zongben, Meng Deyu. Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2023. [code]
Xie Qi, Zhou Minghao, Zhao Qian, Meng Deyu and Xu Zongben. MHF-Net: An interpretable deep network for multispectral and hyperspectral image fusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2020, 44(3): 1457-1473. ( ESI高被引)
Xie Qi, Zhao Qian, Meng Deyu and Xu Zongben. Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 2018, 40(8):1888–1902. (ESI高被引)
Gu Shuhang, Xie Qi, Meng Deyu, Zuo Wangmeng, Feng Xiangchu and Zhang Lei*. Weighted nuclearnorm minimization and its applications to low level vision[J]. International Journal of Computer Vision (IJCV). 2017, 121(2):183–208.(ESI高被引)
Pang Zhiqiang, Wang Hong, Xie Qi*, Meng Deyu, Xu Zongben. TRG-Net: An Interpretable and Controllable Rain Generator. IEEE Transactions on Neural Networks and Learning Systems, 2025.
Sun Zihong, Wang Hong, Xie Qi*, Zheng Yefeng, Meng Deyu. RSF-Conv: Rotation-and-Scale Equivariant Fourier Parameterized Convolution for Retinal Vessel Segmentation. IEEE Transactions on Neural Networks and Learning Systems. 2025
Liu Hanze, Fu Jiahong, Xie Qi*, Meng Deyu. Rotation-Equivariant Self-Supervised Method in Image Denoising, CVPR, 2025. [code]
Bai Yulu , Fu Jiahong, Xie Qi*, Meng Deyu. A Regularization-Guided Equivariant Approach for Image Restoration, CVPR, 2025. [code]
Tan Feiyu, Wang Yuhan, Xie Qi*, et al. DS-Net: A Model Driven Network Framework for Lesion Segmentation on Fundus Image[J]. Knowledge-Based Systems, 2025, 315: 113242.
Xie Qi, Zeng Dong, Zhao Qian, Meng Deyu, Xu Zongben, Liang Zhengrong and Ma Jianhua. Robust low-dose CT sinogram preprocessing via exploiting noise-generating mechanism[J]. IEEE Transactions on Medical Imaging (TMI). 2017, 36(12):2487–2498.
Xie Qi, Zhao Qian, Meng Deyu, Xu Zongben, Gu Shuhang, Zuo Wangmeng and Zhang Lei. Multispectral images denoising by intrinsic tensor sparsity regularization[C]. CVPR, 2016: 1692–1700.
Xie Qi, Zhou Minghao, Zhao Qian, Meng Deyu*, Wangmeng Zuo and Xu Zongben. Multispectral and hyperspectral image fusion by MS/HS fusion net[C]. CVPR, 2019: 1585–1594.
Xie Qi, Zhao Qian, Xu Zongben and Meng Deyu*. Color and Direction-Invariant Nonlocal self-similarity prior and its application to color image denoising[J]. Science China-information Sciences.
Zhou Man, Yan Keyu, Pan Jinshan, Xie Qi, et al. Memory-augmented deep unfolding network for guided image super-resolution[J]. International Journal of Computer Vision (IJCV), 2023, 131(1): 215-242.
Wang Hong#, Xie Qi#, Zhao Qian and Meng Deyu*. A Model-Driven Deep Neural Network for Single Image Rain Removal [C]. CVPR, 2020
Peng Jiangjun#, Xie Qi#, Zhao Qian, Wang Yao, Leung Yee, and Meng Deyu*. Enhanced 3DTV regularization and its applications on HSI denoising and compressed sensing[J]. IEEE Transactions on Image Processing (TIP).
Wang Hong, Wu Yichen, Xie Qi*, et al. Structural residual learning for single image rain removal[J]. Knowledge-Based Systems, 2021, 213: 106595.
Fu Jiahong, Wang Hong, Xie Qi*, Zhao Qiang, Meng Deyu, Xu Zongben. KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution[J]. ECCV, 2022
Wang Hong, Xie Qi*, Zhao Qian, Li Yuexiang, Liang Yong, Zheng Yefeng, Meng Deyu*;RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining;IEEE Transactions on Neural Networks and Learning Systems 2022
Wang Hong, Xie Qi*, Li Yuexiang, et al. Orientation-Shared Convolution Representation for CT Metal Artifact Learning[C]. MICCAI, 2022: 665-675.
Wang Hong, Xie Qi*, Zhao Qian, Li Yuexiang, Liang Yong, Zheng Yefeng, Meng Deyu. RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Wang Hong, Xie Qi, Zeng Dong, et al. OSCNet: Orientation-Shared Convolutional Network for CT Metal Artifact Learning[J]. IEEE Transactions on Medical Imaging, 2023.
Liu Xinyi, Xie Qi, Zhao Qian, Wang Hong, Meng Deyu. Low-light image enhancement by retinex-based algorithm unrolling and adjustment[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023.
Wang Hong, Xie Qi,Wu Yichen, Zhao Qian and Meng Deyu. Single image rain streaks removal: a review and an exploration[J]. International Journal of Machine Learning and Cybernetics. 2020, 1–20.
Zeng Dong, Xie Qi, Cao Wenfei, Lin Jiahui, Zhang Hao, Zhang Shanli, Huang Jing, Bian Zhaoying, Meng Deyu, Xu Zongben, et al. Low-dose dynamic cerebral perfusion computed tomography reconstructionvia kronecker-basis-representation tensor sparsity regularization[J]. IEEE Transactions on Medical Imaging (TMI). 2017, 36(12):2546–2556.
Shu Jun, Xie Qi, Yi Lixuan, Zhao Qian, Zhou Sanping, Xu Zongben and Meng Deyu*. Meta-weight-net: Learning an explicit mapping for sample weighting[C]. NeurIPS, 2019: 1917–1928.
Li Minghan, Xie Qi, Zhao Qian, Wei Wei, Gu Shuhang, Tao Jing and Meng Deyu*. Video rain streak removal by multiscale convolutional sparse coding[C]. CVPR, 2018: 6644–6653.
Zeng Dong, Xie Qi, Bian Zhaoying, et al. Noise suppression for cerebral perfusion CT via intrinsic tensor sparsity regularization: Initial study[C], IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop(NSS/MIC/RTSD). 2016: 1-4.
Hu Zhengyang, Liu Guanzhang, Xie Qi, Xue Jiang, Deyu Meng, Deniz Gunduz. A learnable optimization and regularization approach to massive MIMO CSI feedback[J]. IEEE Transactions on Wireless Communications, 2023.
Gu Shuhang, Zuo Wangmeng, Xie Qi, Meng Deyu, Feng Xiangchu and Zhang Lei. Convolutional sparse coding for image super-resolution[C]. ICCV, 2015: 1823–1831.
Ma Fan, Meng Deyu, Xie Qi, Li Zina and Dong Xuanyi. Self-paced co-training[C]// JMLR. org. Proceedings of the 34th International Conference on Machine Learning-Volume 70: JMLR. org, 2017: 2275–2284.
Wei Wei, Yi Lixuan, Xie Qi, Zhao Qian, Meng Deyu* and Xu Zongben Should we encode rain streaks in video as deterministic or stochastic?[C]. ICCV, 2017: 2516–2525.
Zhao Qian, Meng Deyu*, Kong Xu, Xie Qi, Cao Wenfei, Wang Yao and Xu Zongben. A novel sparsity measure for tensor recovery[C]. ICCV, 2015: 271–279.
Zhao Qian, Meng Deyu*, Jiang Lu, Xie Qi, Xu Zongben, Hauptmann, Alexander G. Self-paced learning for matrix factorization[C]. Twenty-ninth AAAI conference on artificial intelligence, 2015.
Zeng Dong, Lisha Yao, Ge Yongshuai, Li Sui, Xie Qi, Zhang Hao, et al. Full-Spectrum-Knowledge-Aware Tensor Model for Energy-Resolved CT Iterative Reconstruction[J]. IEEE Transactions on Medical Imaging (TMI), 2020.
Sui Li, Zeng Dong, Peng Jiangjun, Bian Zhaoying, Zhang Hao, Xie Qi, Wang Yongbo, et al. An efficient iterative cerebral perfusion CT reconstruction via low-rank tensor decomposition with spatial–temporal total variation regularization[J]. IEEE Transactions on Medical Imaging (TMI), 2018, 38(2): 360-370.
Meng Mingqiang, Li Sui, Yao Lisha, Li Danyang, Zhu Manman, Gao Qi, Xie Qi, Zhao Qian, Bian Zhaoying, Huang Jing, Meng Deyu, et al. Semi-supervised learned sinogram restoration network for low-dose CT image reconstruction[C], Medical Imaging 2020: Physics of Medical Imaging. International Society for Optics and Photonics, 2020, 11312: 113120B.
专著发表:
谢琦; 图像数据先验的数学建模及其应用, CCF优博丛书, 机械工业出版社, 2024

专利发表: