在IEEETCYB发表论文

Meta-SR: A Magnification-Arbitrary Network for Super-Resolution Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Tieniu Tan, Jian Sun [ pdf ]

Blind Super-Resolution With Iterative Kernel Correction Jinjin Gu, Hannan Lu, Wangmeng Zuo, Chao Dong [ pdf ]

Camera Lens Super-Resolution Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha, Feng Wu [ pdf ], [ supp ]

Deep Plug-And-Play Super-Resolution for Arbitrary Blur Kernels Kai Zhang, Wangmeng Zuo, Lei Zhang [ pdf ]

Towards Real Scene Super-Resolution With Raw Images Xiangyu Xu, Yongrui Ma, Wenxiu Sun [ pdf ]

ODE-Inspired Network Design for Single Image Super-Resolution Xiangyu He, Zitao Mo, Peisong Wang, Yang Liu, Mingyuan Yang, Jian Cheng [ pdf ], [ supp ]

Feedback Network for Image Super-Resolution Zhen Li, Jinglei Yang, Zheng Liu, Xiaomin Yang, Gwanggil Jeon, Wei Wu [ pdf ], [ supp ]

Recurrent Back-Projection Network for Video Super-Resolution Muhammad Haris, Gregory Shakhnarovich, Norimichi Ukita [ pdf ], [ supp ]

Image Super-Resolution by Neural Texture Transfer Zhifei Zhang, Zhaowen Wang, Zhe Lin, Hairong Qi [ pdf ]

Natural and Realistic Single Image Super-Resolution With Explicit Natural Manifold Discrimination Jae Woong Soh, Gu Yong Park, Junho Jo, Nam Ik Cho [ pdf ], [ supp ]

3D Appearance Super-Resolution With Deep Learning Yawei Li, Vagia Tsiminaki, Radu Timofte, Marc Pollefeys, Luc Van Gool [ pdf ], [ supp ]

Fast Spatio-Temporal Residual Network for Video Super-Resolution Sheng Li, Fengxiang He, Bo Du, Lefei Zhang, Yonghao Xu, Dacheng Tao [ pdf ], [ supp ]

Residual Networks for Light Field Image Super-Resolution Shuo Zhang, Youfang Lin, Hao Sheng [ pdf ]

Second-Order Attention Network for Single Image Super-Resolution Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang [ pdf ], [ pdf ]

Hyperspectral Image Super-Resolution With Optimized RGB Guidance Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang [ pdf ]

Learning Parallax Attention for Stereo Image Super-Resolution Longguang Wang, Yingqian Wang, Zhengfa Liang, Zaiping Lin, Jungang Yang, Wei An, Yulan Guo [ pdf ], [ supp ]

Face Super-resolution Guided by Facial Component Heatmaps Xin Yu, Basura Fernando, Bernard Ghanem, Fatih Porikli, Richard Hartley [ pdf ]

Image Super-Resolution Using Very Deep Residual Channel Attention Networks Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, Yun Fu [ pdf ]

Super-Resolution and Sparse View CT Reconstruction Guangming Zang, Mohamed Aly, Ramzi Idoughi, Peter Wonka, Wolfgang Heidrich [ pdf ]

Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network Namhyuk Ahn, Byungkon Kang, Kyung-Ah Sohn [ pdf ]

SRFeat: Single Image Super-Resolution with Feature Discrimination Seong-Jin Park, Hyeongseok Son, Sunghyun Cho, Ki-Sang Hong, Seungyong Lee [ pdf ]

To learn image super-resolution, use a GAN to learn how to do image degradation first Adrian Bulat, Jing Yang, Georgios Tzimiropoulos [ pdf ]

Multi-scale Residual Network for Image Super-Resolution Juncheng Li, Faming Fang, Kangfu Mei, Guixu Zhang [ pdf ]

Super-FAN: Integrated Facial Landmark Localization and Super-Resolution of Real-World Low Resolution Faces in Arbitrary Poses With GANs Adrian Bulat, Georgios Tzimiropoulos [ pdf ] [ Supp ]

Fight Ill-Posedness With Ill-Posedness: Single-Shot Variational Depth Super-Resolution From Shading Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers [ pdf ] [ Supp ]

Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform Xintao Wang, Ke Yu, Chao Dong, Chen Change Loy [ pdf ]

Fast and Accurate Single Image Super-Resolution via Information Distillation Network Zheng Hui, Xiumei Wang, Xinbo Gao [ pdf ]

Image Super-Resolution via Dual-State Recurrent Networks Wei Han, Shiyu Chang, Ding Liu, Mo Yu, Michael Witbrock, Thomas S. Huang [ pdf ]

Deep Back-Projection Networks for Super-Resolution Muhammad Haris, Gregory Shakhnarovich, Norimichi Ukita [ pdf ] [ Supp ]

Residual Dense Network for Image Super-Resolution Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, Yun Fu [ pdf ]

FSRNet: End-to-End Learning Face Super-Resolution With Facial Priors Yu Chen, Ying Tai, Xiaoming Liu, Chunhua Shen, Jian Yang [ pdf ]

Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution Ying Qu, Hairong Qi, Chiman Kwan [ pdf ]

“Zero-Shot” Super-Resolution Using Deep Internal Learning Assaf Shocher, Nadav Cohen, Michal Irani [ pdf ]

Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation Younghyun Jo, Seoung Wug Oh, Jaeyeon Kang, Seon Joo Kim [ pdf ] [ Supp ]

Learning a Single Convolutional Super-Resolution Network for Multiple Degradations Kai Zhang, Wangmeng Zuo, Lei Zhang [ pdf ]

Feature Super-Resolution: Make Machine See More Clearly Weimin Tan, Bo Yan, Bahetiyaer Bare [ pdf ]

Frame-Recurrent Video Super-Resolution Mehdi S. M. Sajjadi, Raviteja Vemulapalli, Matthew Brown [ pdf ]

Temporal Shape Super-Resolution by Intra-Frame Motion Encoding Using High-Fps Structured Light Yuki Shiba, Satoshi Ono, Ryo Furukawa, Shinsaku Hiura, Hiroshi Kawasaki [ pdf ] [ Supp ] [ video ]

Robust Video Super-Resolution With Learned Temporal Dynamics Ding Liu, Zhaowen Wang, Yuchen Fan, Xianming Liu, Zhangyang Wang, Shiyu Chang, Thomas Huang [ pdf ]

Detail-Revealing Deep Video Super-Resolution Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia [ pdf ] [ video ]

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis Mehdi S. M. Sajjadi, Bernhard Scholkopf, Michael Hirsch [ pdf ] [ Supp ][ video ]

Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution From a Blurred Image Sequence Haesol Park, Kyoung Mu Lee [ pdf ] [ Supp ]

Image Super-Resolution Using Dense Skip Connections Tong Tong, Gen Li, Xiejie Liu, Qinquan Gao [ pdf ]

Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, Ming-Hsuan Yang [ pdf ]

Image Super-Resolution via Deep Recursive Residual Network Ying Tai, Jian Yang, Xiaoming Liu [ pdf ]

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi [ pdf ] [ poster ] [ video ]

Real-Time Video Super-Resolution With Spatio-Temporal Networks and Motion Compensation Jose Caballero, Christian Ledig, Andrew Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, Wenzhe Shi [ pdf ] [ poster ]

Hyperspectral Image Super-Resolution via Non-Local Sparse Tensor Factorization Renwei Dian, Leyuan Fang, Shutao Li [ pdf ] [ poster ]

Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding Yawen Huang, Ling Shao, Alejandro F. Frangi [ pdf ] [ poster ]

Reference Guided Deep Super-Resolution via Manifold Localized External Compensation Wenhan Yang, Sifeng Xia, Jiaying Liu, and Zongming Guo Accepted by IEEE Trans. on Circuit System for Video Technology (TCSVT), June 2018. [ project ]

Joint-Feature Guided Depth Map Super-Resolution With Face Priors Shuai Yang, Jiaying Liu, Yuming Fang, and Zongming Guo IEEE Trans. on Cybernetics (TCYB), Vol.48, No.1, pp.399-411, Jan. 2018. [ project ]

Deep Edge Guided Recurrent Residual Learning for Image Super-Resolution Wenhan Yang, Jiashi Feng, Jianchao Yang, Fang Zhao, Jiaying Liu, Zongming Guo and Shuicheng Yan IEEE Trans. on Image Processing (TIP), Vol.26, No.12, pp.5895-5907, Dec. 2017. [ project ]

Retrieval Compensated Group Structured Sparsity for Image Super-Resolution Jiaying Liu, Wenhan Yang, Xinfeng Zhang, and Zongming Guo IEEE Trans. on Multimedia (TMM), Vol.19, No.2, pp.302-216, Feb. 2017. [ project ]

ECCV2016 Accelerating the Super-Resolution Convolutional Neural Network Chao Dong, Chen Change Loy, Xiaoou Tang [ project ]

Perceptual Losses for Real-Time Style Transfer and Super-Resolution Justin Johnson, Alexandre Alahi, Li Fei-Fei [ pdf ]

End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks Yifan Wang, Lijun Wang, Hongyu Wang, Peihua Li [ pdf ]

Deeply-Recursive Convolutional Network for Image Super-Resolution Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee [ pdf ]

Accurate Image Super-Resolution Using Very Deep Convolutional Networks Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee [ pdf ]

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi, Jose Caballero, Ferenc Huszar, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, Zehan Wang [ pdf ]

Image Super-Resolution Using Deep Convolutional Networks Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) SRCNN [ project ] [ pdf ] [ supplementary material ]

Neighborhood Regression for Edge-Preserving Image Super-Resolution Yanghao Li, Jiaying Liu, Wenhan Yang and Zongming Guo IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, Apr. 2015. [ project ]

Learning a Deep Convolutional Network for Image Super-Resolution Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang ECCV 2014 SRCNN [ project ] [ pdf ]

Super-Resolution From a Single Image Daniel Glasner, Shai Bagon, Michal Irani ICCV 2009 [ project ] [ pdf ]

Video Super-Resolution Based on Spatial-Temporal Recurrent Neural Networks Wenhan Yang, Jiashi Feng, Guosen Xie, Jiaying Liu, Zongming Guo and Shuicheng Yan Computer Vision and Image Understanding (CVIU), Vol.168, pp.79-92, March. 2018. [ project ]

Video Super-Resolution With Convolutional Neural Networks Armin Kappeler ; Seunghwan Yoo ; Qiqin Dai ; Aggelos K. Katsaggelos IEEE Transactions on Computational Imaging [ pdf ]

High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network Wenjia Xu; Guangluan XU; Yang Wang; Xian Sun; Daoyu Lin; Yirong WU IGARSS 2018 - 2018 IEEE International Geoscience and Remote SensingSymposium [ pdf ]

中国地质大学朱祺琪老师怎么样介绍如下：

朱祺琪，博士，中国地质大学(武汉)地理与信息工程学院副教授，硕士生导师,“地大学者”青年拔尖人才。

2013年免试攻读武汉大学硕士学位，2015年硕博连读提前攻博，师从李德仁院士、钟燕飞教授与张良培教授，2018年6月毕业于武汉大学测绘遥感信息工程国家重点实验室，获摄影测量与遥感专业工学博士学位。2018年7月以“地大学者”青年优秀人才引进至中国地质大学（武汉）地理与信息工程学院。

致力于遥感大数据智能提取分析及应用方向的研究，在RSE、IEEE TCYB、ISPRS P&RS、IEEE TGRS等国际地学、遥感和信息处理领域权威期刊上发表一作/通讯论文三十余篇，5篇SCI论文入选ESI全球1%高被引论文；获2022年国家地理信息科技进步奖一等奖，2022年全国大学生测绘学科创新创业智能大赛一等奖指导教师，第十三届青年教师教学竞赛特等奖。

第三十二届研究生科技论文报告会优秀指导老师；入选中国地质大学（武汉）2022"十佳班主任"；连续四年获中国地质大学（武汉）本科毕业论文优秀指导教师奖。

已主持国家重点研发计划项目子课题、国家自然科学基金面上项目等科研项目十余项。担任SCI 期刊Geo-spatial Information Science编委，以及Remote Sensing等SCI期刊的客座编辑；担任Remote Sensing of Environment、ISPRS Journal of Photogrammetry and Remote Sensing、IEEE Transaction on Geoscience and Remote Sensing。

IEEE Transactions on Knowledge and Data Engineering、IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing、IEEE Geoscience and Remote Sensing Letter等遥感、计算机领域国际权威SCI期刊的审稿人。

指导研究生获国家奖学金、信才等专项奖学金，获校级研究生科报会特等奖；带领的研究组积极为学生提供国内外学术交流，多名组内学生受邀担任国际遥感会议IGARSS的会议联合主席；带领本科生成功立项“大学生创新创业训练计划”国家级项目8项，独立撰写SCI论文。

研究生毕业后大多进入武汉大学、中山大学、中国地质大学（武汉）等国内外著名高校和腾讯、华为、百度等知名互联网公司以及测绘、城市等事业单位任职和深造。