Most cited papers in Video Surveillance and Tracking Methods
What are the most cited papers in Video Surveillance and Tracking Methods?
The most cited paper in Video Surveillance and Tracking Methods is "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (Shaoqing Ren, Kaiming He, Ross Girshick et al., 2016), with 55,999 citations. Next come "Histograms of Oriented Gradients for Human Detection" (32,222) and "Fast R-CNN" (28,569).
Showing 50 of 98 papers. Every paper with more than 1,860 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren, Kaiming He, Ross Girshick et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 6 Jun 2016 | 55,999 |
| 2 | Histograms of Oriented Gradients for Human Detection Navneet Dalal, Bill Triggs | 27 Jul 2005 | 32,222 |
| 3 | Fast R-CNN Ross Girshick | Dec 2015 | 28,569 |
| 4 | Focal Loss for Dense Object Detection Tsung-Yi Lin, Priya Goyal, Ross Girshick et al. | Oct 2017 | 27,432 |
| 5 | The Cityscapes Dataset for Semantic Urban Scene Understanding Marius Cordts, Mohamed Omran, Sebastian Ramos et al. | Jun 2016 | 12,301 |
| 6 | Vision meets robotics: The KITTI dataset Andreas Geiger, Philip Lenz, Christoph Stiller et al. · The International Journal of Robotics Research | 23 Aug 2013 | 10,105 |
| 7 | Learning Spatiotemporal Features with 3D Convolutional Networks Du Tran, Lubomir Bourdev, Rob Fergus et al. | Dec 2015 | 9,921 |
| 8 | ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin et al. | Jun 2018 | 9,334 |
| 9 | Domain-Adversarial Training of Neural Networks Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan et al. · Advances in computer vision and pattern recognition | 2017 | 7,721 |
| 10 | Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields Zhe Cao, Tomas Simon, Shih-En Wei et al. | Jul 2017 | 7,513 |
| 11 | Good features to track Jianbo Shi, Tomasi | 1994 | 7,017 |
| 12 | Dual Attention Network for Scene Segmentation Jun Fu, Jing Liu, Haijie Tian et al. | Jun 2019 | 6,973 |
| 13 | Adaptive background mixture models for real-time tracking Chris Stauffer, W. Eric L. Grimson | 20 Jan 2003 | 6,956 |
| 14 | Large-Scale Video Classification with Convolutional Neural Networks Andrej Karpathy, George D. Toderici, Sanketh Shetty et al. | Jun 2014 | 6,403 |
| 15 | High-Speed Tracking with Kernelized Correlation Filters João F. Henriques, Rui Caseiro, Pedro Martins et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | Aug 2014 | 5,866 |
| 16 | Indoor Segmentation and Support Inference from RGBD Images Nathan Silberman, Derek Hoiem, Pushmeet Kohli et al. · Lecture notes in computer science | 2012 | 5,770 |
| 17 | Two-Stream Convolutional Networks for Action Recognition in Videos Karen Simonyan, Andrew Zisserman · arXiv (Cornell University) | 9 Jun 2014 | 5,362 |
| 18 | OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields Zhe Cao, Gines Hidalgo, Tomas Simon et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 17 Jul 2019 | 5,255 |
| 19 | A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects Zewen Li, Fan Liu, Wenjie Yang et al. · IEEE Transactions on Neural Networks and Learning Systems | 10 Jun 2021 | 5,150 |
| 20 | Deep Face Recognition Omkar Parkhi, Andrea Vedaldi, Andrew Zisserman | 2015 | 5,143 |
| 21 | Simple online and realtime tracking with a deep association metric Nicolai Wojke, Alex Bewley, Dietrich W. R. Paulus | Sep 2017 | 4,989 |
| 22 | Object tracking Alper Yılmaz, Omar Javed, Mubarak A. Shah · ACM Computing Surveys | 25 Dec 2006 | 4,732 |
| 23 | Scalable Person Re-identification: A Benchmark Liang Zheng, Liyue Shen, Lu Tian et al. | Dec 2015 | 4,710 |
| 24 | Kernel-based object tracking Dorin Comaniciu, Visvanathan Ramesh, Peter Meer · IEEE Transactions on Pattern Analysis and Machine Intelligence | May 2003 | 4,582 |
| 25 | Fully-Convolutional Siamese Networks for Object Tracking Luca Bertinetto, Jack Valmadre, João F. Henriques et al. · Lecture notes in computer science | 2016 | 4,443 |
| 26 | DETRs Beat YOLOs on Real-time Object Detection Y. Zhao, Wenyu Lv, Shangliang Xu et al. | 16 Jun 2024 | 4,356 |
| 27 | Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia, Evan Shelhamer, Jeff Donahue et al. · arXiv (Cornell University) | 20 Jun 2014 | 4,297 |
| 28 | Online Object Tracking: A Benchmark Yi Wu, Jongwoo Lim, Ming–Hsuan Yang | Jun 2013 | 4,164 |
| 29 | Simple online and realtime tracking Alex Bewley, Zongyuan Ge, Lionel Ott et al. | 17 Aug 2016 | 4,156 |
| 30 | Temporal Segment Networks: Towards Good Practices for Deep Action Recognition Limin Wang, Yuanjun Xiong, Zhe Wang et al. · Lecture notes in computer science | 2016 | 4,010 |
| 31 | HMDB: A large video database for human motion recognition Hilde Kuehne, Hueihan Jhuang, Estíbaliz Garrote et al. | Nov 2011 | 3,990 |
| 32 | Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments Catalin Ionescu, Dragos Papava, Vlad Olaru et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 31 Jan 2014 | 3,786 |
| 33 | Social LSTM: Human Trajectory Prediction in Crowded Spaces Alexandre Alahi, Kratarth Goel, Vignesh Ramanathan et al. | Jun 2016 | 3,626 |
| 34 | Action Recognition with Improved Trajectories Heng Wang, Cordelia Schmid | Dec 2013 | 3,570 |
| 35 | Real-time human pose recognition in parts from single depth images Jamie Shotton, Andrew W Fitzgibbon, Mat Cook et al. | Jun 2011 | 3,551 |
| 36 | Object Tracking Benchmark Yi Wu, Jongwoo Lim, Ming–Hsuan Yang · IEEE Transactions on Pattern Analysis and Machine Intelligence | 2015 | 3,506 |
| 37 | Deep Learning for Computer Vision: A Brief Review Athanasios S. Voulodimos, Nikolaos D. Doulamis, Anastasios D. Doulamis et al. · Computational Intelligence and Neuroscience | 2018 | 3,387 |
| 38 | Visual object tracking using adaptive correlation filters D.S. Bolme, J. Ross Beveridge, Bruce A. Draper et al. | Jun 2010 | 3,379 |
| 39 | Tracking-Learning-Detection Zdenek Kalal, Krystian Mikolajczyk, Jiřı́ Matas · IEEE Transactions on Pattern Analysis and Machine Intelligence | 13 Dec 2011 | 3,308 |
| 40 | SUN database: Large-scale scene recognition from abbey to zoo Jianxiong Xiao, James H. Hays, Krista A. Ehinger et al. | Jun 2010 | 3,289 |
| 41 | Pedestrian Detection: An Evaluation of the State of the Art Piotr Dollár, Christian Wojek, Bernt Schiele et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 15 Aug 2011 | 3,283 |
| 42 | Learning patterns of activity using real-time tracking Chris Stauffer, W. Eric L. Grimson · IEEE Transactions on Pattern Analysis and Machine Intelligence | 2000 | 3,248 |
| 43 | Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren et al. · Lecture notes in computer science | 2014 | 3,178 |
| 44 | Incremental Learning for Robust Visual Tracking David A. Ross, Jongwoo Lim, Ruei-Sung Lin et al. · International Journal of Computer Vision | 16 Aug 2007 | 3,114 |
| 45 | High Performance Visual Tracking with Siamese Region Proposal Network Bo Hu Li, Junjie Yan, Wei Wu et al. | Jun 2018 | 3,035 |
| 46 | CosFace: Large Margin Cosine Loss for Deep Face Recognition Hao Wang, Yitong Wang, Zheng Zhou et al. | Jun 2018 | 2,962 |
| 47 | Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics Keni Bernardin, Rainer Stiefelhagen · EURASIP Journal on Image and Video Processing | 2008 | 2,953 |
| 48 | Real-time tracking of non-rigid objects using mean shift Dorin Comaniciu, Visvanathan Ramesh, Peter Meer | 7 Nov 2002 | 2,928 |
| 49 | A discriminatively trained, multiscale, deformable part model Pedro F. Felzenszwalb, David McAllester, Deva Ramanan | Jun 2008 | 2,928 |
| 50 | Performance Measures and a Data Set for Multi-target, Multi-camera Tracking Ergys Ristani, Francesco Solera, Roger S. Zou et al. · Lecture notes in computer science | 2016 | 2,914 |
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.