Most cited papers in Advanced Image Processing Techniques
What are the most cited papers in Advanced Image Processing Techniques?
The most cited paper in Advanced Image Processing Techniques is "ImageNet classification with deep convolutional neural networks" (Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton, 2017), with 75,634 citations. Next come "Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks" (22,468) and "Nonlinear total variation based noise removal algorithms" (15,969).
Showing 50 of 98 papers. Every paper with more than 1,719 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | ImageNet classification with deep convolutional neural networks Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton · Communications of the ACM | 24 May 2017 | 75,634 |
| 2 | Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks Jun-Yan Zhu, Taesung Park, Phillip Isola et al. | Oct 2017 | 22,468 |
| 3 | Nonlinear total variation based noise removal algorithms L. Rudin, Stanley Osher, Emad Fatemi · Physica D Nonlinear Phenomena | Nov 1992 | 15,969 |
| 4 | High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach, Andreas Blattmann, Dominik Lorenz et al. · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | Jun 2022 | 15,702 |
| 5 | The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Zhang, Phillip Isola, Alexei A. Efros et al. | Jun 2018 | 13,833 |
| 6 | Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network Christian Ledig, Lucas Theis, Ferenc Huszár et al. | Jul 2017 | 12,615 |
| 7 | Perceptual Losses for Real-Time Style Transfer and Super-Resolution Justin M. Johnson, Alexandre Alahi, Li Fei-Fei · Lecture notes in computer science | 2016 | 10,170 |
| 8 | Image Super-Resolution Using Deep Convolutional Networks Chao Dong, Chen Change Loy, Kaiming He et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 2 Jun 2015 | 10,149 |
| 9 | Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising Kai Zhang, Wangmeng Zuo, Yunjin Chen et al. · IEEE Transactions on Image Processing | Feb 2017 | 9,223 |
| 10 | Accurate Image Super-Resolution Using Very Deep Convolutional Networks Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee | Jun 2016 | 7,784 |
| 11 | A Non-Local Algorithm for Image Denoising Antoni Buades, B. Coll, Jean‐Michel Morel | 27 Jul 2005 | 7,245 |
| 12 | Fast approximate energy minimization via graph cuts Yuri Boykov, Olga Veksler, Ramin Zabih · IEEE Transactions on Pattern Analysis and Machine Intelligence | 2001 | 7,066 |
| 13 | Single Image Haze Removal Using Dark Channel Prior Kaiming He, Jian Cheng Sun, Xiaoou Tang · IEEE Transactions on Pattern Analysis and Machine Intelligence | 15 Sep 2010 | 6,281 |
| 14 | Learning a Deep Convolutional Network for Image Super-Resolution Chao Dong, Chen Change Loy, Kaiming He et al. · Lecture notes in computer science | 2014 | 5,746 |
| 15 | Image Super-Resolution Using Very Deep Residual Channel Attention Networks Yulun Zhang, Kunpeng Li, Kai Li et al. · Lecture notes in computer science | 2018 | 5,660 |
| 16 | 3D Gaussian Splatting for Real-Time Radiance Field Rendering Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler et al. · ACM Transactions on Graphics | 26 Jul 2023 | 5,593 |
| 17 | Image Super-Resolution Via Sparse Representation Jianchao Yang, John N. Wright, Thomas S. Huang et al. · IEEE Transactions on Image Processing | 26 May 2010 | 5,333 |
| 18 | Least Squares Generative Adversarial Networks Xudong Mao, Qing Li, Haoran Xie et al. | Oct 2017 | 5,285 |
| 19 | Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization Xun Cheng Huang, Serge Belongie | Oct 2017 | 5,077 |
| 20 | Wasserstein Generative Adversarial Networks Martín Arjovsky, Soumith Chintala, Léon Bottou · International Conference on Machine Learning | 17 Jul 2017 | 5,047 |
| 21 | Image Quality Metrics: PSNR vs. SSIM Alain Horé, Djemel Ziou | Aug 2010 | 4,676 |
| 22 | SwinIR: Image Restoration Using Swin Transformer Jingyun Liang, Jiezhang Cao, Guolei Sun et al. | Oct 2021 | 4,644 |
| 23 | Generative Adversarial Networks: An Overview Antonia Creswell, Tom White, Vincent Dumoulin et al. · IEEE Signal Processing Magazine | 2018 | 4,566 |
| 24 | Multimodality image registration by maximization of mutual information Frederik Maes, Andre M. F. Collignon, Dirk Vandermeulen et al. · IEEE Transactions on Medical Imaging | Apr 1997 | 4,564 |
| 25 | Stereo Processing by Semiglobal Matching and Mutual Information Heiko Hirschmüller · IEEE Transactions on Pattern Analysis and Machine Intelligence | 20 Dec 2007 | 4,328 |
| 26 | Performance of optical flow techniques John A. Barron, David J. Fleet, Steven S. Beauchemin · International Journal of Computer Vision | Feb 1994 | 4,306 |
| 27 | Bayesian-Based Iterative Method of Image Restoration* William Hadley Richardson · Journal of the Optical Society of America | 1972 | 4,234 |
| 28 | NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study Eirikur Agustsson, Radu Timofte | Jul 2017 | 4,203 |
| 29 | Residual Dense Network for Image Super-Resolution Yulun Zhang, Yapeng Tian, Yu Xiang George Kong et al. | Jun 2018 | 4,180 |
| 30 | ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks Xintao Wang, Ke Yu, Shixiang Wu et al. · Lecture notes in computer science | 2019 | 4,026 |
| 31 | Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan et al. · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | Jun 2022 | 4,022 |
| 32 | Accelerating the Super-Resolution Convolutional Neural Network Chao Dong, Chen Change Loy, Xiaoou Tang · Lecture notes in computer science | 2016 | 3,666 |
| 33 | Single image super-resolution from transformed self-exemplars Jia‐Bin Huang, Abhishek Singh, Narendra Ahuja | Jun 2015 | 3,607 |
| 34 | On Single Image Scale-Up Using Sparse-Representations Roman Zeyde, Michael Elad, Matan Protter · Lecture notes in computer science | 2012 | 3,439 |
| 35 | DehazeNet: An End-to-End System for Single Image Haze Removal Bolun Cai, Xiangmin Xu, Kui Jia et al. · IEEE Transactions on Image Processing | 10 Aug 2016 | 3,386 |
| 36 | FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks Eddy Ilg, N. Michael Mayer, Tonmoy Saikia et al. | Jul 2017 | 3,369 |
| 37 | Unsupervised Monocular Depth Estimation with Left-Right Consistency Clément Godard, Oisin Mac Aodha, Gabriel Brostow | Jul 2017 | 3,330 |
| 38 | Deeply-Recursive Convolutional Network for Image Super-Resolution Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee | Jun 2016 | 3,132 |
| 39 | Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution Wei‐Sheng Lai, Jia‐Bin Huang, Narendra Ahuja et al. | Jul 2017 | 3,096 |
| 40 | LIME: Low-Light Image Enhancement via Illumination Map Estimation Xiaojie Guo, Yu Li, Haibin Ling · IEEE Transactions on Image Processing | 14 Dec 2016 | 3,001 |
| 41 | Scope of validity of PSNR in image/video quality assessment Quan Huynh‐Thu, M. Ghanbari · Electronics Letters | 19 Jun 2008 | 2,946 |
| 42 | Loss Functions for Image Restoration With Neural Networks Hang Zhao, Orazio Gallo, Iuri Frosio et al. · IEEE Transactions on Computational Imaging | 24 Dec 2016 | 2,716 |
| 43 | High Accuracy Optical Flow Estimation Based on a Theory for Warping Thomas Brox, Andrés Bruhn, Nils Papenberg et al. · Lecture notes in computer science | 2004 | 2,614 |
| 44 | EnlightenGAN: Deep Light Enhancement Without Paired Supervision Yifan Jiang, Xinyu Gong, Ding Liu et al. · IEEE Transactions on Image Processing | 2021 | 2,612 |
| 45 | RAFT: Recurrent All-Pairs Field Transforms for Optical Flow Zachary Teed, Jia Hao Deng · Lecture notes in computer science | 2020 | 2,596 |
| 46 | Multimodal Unsupervised Image-to-Image Translation Xun Cheng Huang, Ming-Yu Liu, Serge Belongie et al. · Lecture notes in computer science | 2018 | 2,591 |
| 47 | Generative Image Inpainting with Contextual Attention Jiahui Yu, Zhe Lin, Jimei Yang et al. | Jun 2018 | 2,537 |
| 48 | Example-based super-resolution William T. Freeman, Thouis R. Jones, Egon C. Pasztor · IEEE Computer Graphics and Applications | 2002 | 2,532 |
| 49 | Image Super-Resolution via Deep Recursive Residual Network Ying Yu Tai, Jian Jun Yang, Xiaoming Liu | Jul 2017 | 2,514 |
| 50 | Image Inpainting for Irregular Holes Using Partial Convolutions Guilin Liu, Fitsum A. Reda, Kevin J. Shih et al. · Lecture notes in computer science | 2018 | 2,442 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.