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Tracking objects of interest in a video is one of the most popular and widely applicable problems in computer vision.
The hungarian method for the assignment problem
Harold W Kuhn · 1955
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A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
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Evaluating multiple object tracking performance: the clear mot metrics
Keni Bernardin and Rainer Stiefelhagen · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Cascade object detection with deformable part models
Pedro F Felzenszwalb, Ross B Girshick, and David McAllester · 2010
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Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
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Towards understanding action recognition
H. Jhuang, J. Gall, S. Zuffi, C. Schmid, and M. J. Black · 2013
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Online object tracking: A benchmark
Yi Wu, Jongwoo Lim, and Ming-Hsuan Yang · 2013
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High-speed tracking with kernelized correlation filters
João F Henriques, Rui Caseiro, Pedro Martins, and Jorge Batista · 2014
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Deepreid: Deep filter pairing neural network for person re-identification
Wei Li, Rui Zhao, Tong Xiao, and Xiaogang Wang · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Do convnets learn correspondence?
Jonathan Long, Ning Zhang, and Trevor Darrell · 2014
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Flownet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Encoding color information for visual tracking: Algorithms and benchmark
Pengpeng Liang, Erik Blasch, and Haibin Ling · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Unsupervised learning of visual representations using videos
Xiaolong Wang and Abhinav Gupta · 2015
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Scalable person re-identification: A benchmark
Liang Zheng, Liyue Shen, Lu Tian, Shengjin Wang, Jingdong Wang, and Qi Tian · 2015
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Staple: Complementary learners for real-time tracking
Luca Bertinetto, Jack Valmadre, Stuart Golodetz, Ondrej Miksik, and Philip HS Torr · 2016
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Fully-convolutional siamese networks for object tracking
Luca Bertinetto, Jack Valmadre, Joao F Henriques, Andrea Vedaldi, and Philip HS Torr · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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A novel performance evaluation methodology for single-target trackers
Matej Kristan, Jiri Matas, Aleš Leonardis, Tomáš Vojíř, Roman Pflugfelder, Gustavo Fernandez, Georg Nebehay, Fatih Porikli, and Luka Čehovin · 2016
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Mot16: A benchmark for multi-object tracking
Anton Milan, Laura Leal-Taixé, Ian Reid, Stefan Roth, and Konrad Schindler · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
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Performance measures and a data set for multi-target, multi-camera tracking
Ergys Ristani, Francesco Solera, Roger Zou, Rita Cucchiara, and Carlo Tomasi · 2016
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Convolutional pose machines
Shih-En Wei, Varun Ramakrishna, Takeo Kanade, and Yaser Sheikh · 2016
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Exploit all the layers: Fast and accurate cnn object detector with scale dependent pooling and cascaded rejection classifiers
Fan Yang, Wongun Choi, and Yuanqing Lin · 2016
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Eco: Efficient convolution operators for tracking
Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, and Michael Felsberg · 2017
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Learning background-aware correlation filters for visual tracking
Hamed Kiani Galoogahi, Ashton Fagg, and Simon Lucey · 2017
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Multiple people tracking by lifted multicut and person re-identification
Siyu Tang, Mykhaylo Andriluka, Bjoern Andres, and Bernt Schiele · 2017
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End-to-end representation learning for correlation filter based tracking
Jack Valmadre, Luca Bertinetto, Joao Henriques, Andrea Vedaldi, and Philip HS Torr · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Dcfnet: Discriminant correlation filters network for visual tracking
Qiang Wang, Jin Gao, Junliang Xing, Mengdan Zhang, and Weiming Hu · 2017
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Simple online and realtime tracking with a deep association metric
Nicolai Wojke, Alex Bewley, and Dietrich Paulus · 2017
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Split-brain autoencoders: Unsupervised learning by cross-channel prediction
Richard Zhang, Phillip Isola, and Alexei A Efros · 2017
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Scene parsing through ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
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Posetrack: A benchmark for human pose estimation and tracking
Mykhaylo Andriluka, Umar Iqbal, Eldar Insafutdinov, Leonid Pishchulin, Anton Milan, Juergen Gall, and Bernt Schiele · 2018
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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
Cited alongside, same era.
Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Multi-domain pose network for multi-person pose estimation and tracking
Hengkai Guo, Tang Tang, Guozhong Luo, Riwei Chen, Yongchen Lu, and Linfu Wen · 2018
Cited alongside, same era.
Deep spatial feature reconstruction for partial person re-identification: Alignment-free approach
Lingxiao He, Jian Liang, Haiqing Li, and Zhenan Sun · 2018
Cited alongside, same era.
Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
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Mot20: A benchmark for multi object tracking in crowded scenes
Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian Reid, Stefan Roth, Konrad Schindler, and Laura Leal-Taixé · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Mat: Motion-aware multi-object tracking
Shoudong Han, Piao Huang, Hongwei Wang, En Yu, Donghaisheng Liu, Xiaofeng Pan, and Jun Zhao · 2020
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Bo Li, Junjie Yan, Wei Wu, Zheng Zhu, and Xiaolin Hu · 2018
Cited alongside, same era.
Real-time multiple people tracking with deeply learned candidate selection and person re-identification
Chen Long, Ai Haizhou, Zhuang Zijie, and Shang Chong · 2018
Cited alongside, same era.
Long-term visual object tracking benchmark
Abhinav Moudgil and Vineet Gandhi · 2018
Cited alongside, same era.
Trackingnet: A large-scale dataset and benchmark for object tracking in the wild
Matthias Muller, Adel Bibi, Silvio Giancola, Salman Alsubaihi, and Bernard Ghanem · 2018
Cited alongside, same era.
A top-down approach to articulated human pose estimation and tracking
Guanghan Ning, Ping Liu, Xiaochuan Fan, and Chi Zhang · 2018
Cited alongside, same era.
Features for multi-target multi-camera tracking and re-identification
Ergys Ristani and Carlo Tomasi · 2018
Cited alongside, same era.
Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline)
Yifan Sun, Liang Zheng, Yi Yang, Qi Tian, and Shengjin Wang · 2018
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Space-time correspondence as a contrastive random walk
Allan Jabri, Andrew Owens, and Alexei A Efros · 2020
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Mast: A memory-augmented self-supervised tracker
Zihang Lai, Erika Lu, and Weidi Xie · 2020
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Rethinking the competition between detection and reid in multi-object tracking
Chao Liang, Zhipeng Zhang, Yi Lu, Xue Zhou, Bing Li, Xiyong Ye, and Jianxiao Zou · 2020
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Self-emd: Self-supervised object detection without imagenet
Songtao Liu, Zeming Li, and Jian Sun · 2020
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Hota: A higher order metric for evaluating multi-object tracking
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip Torr, Andreas Geiger, Laura Leal-Taixé, and Bastian Leibe · 2020
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D3s-a discriminative single shot segmentation tracker
Alan Lukezic, Jiri Matas, and Matej Kristan · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Lighttrack: A generic framework for online top-down human pose tracking
Guanghan Ning and Heng Huang · 2020
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Tubetk: Adopting tubes to track multi-object in a one-step training model
Bo Pang, Yizhuo Li, Yifan Zhang, Muchen Li, and Cewu Lu · 2020
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Chained-tracker: Chaining paired attentive regression results for end-to-end joint multiple-object detection and tracking
Jinlong Peng, Changan Wang, Fangbin Wan, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, and Yanwei Fu · 2020
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15 keypoints is all you need
Michael Snower, Asim Kadav, Farley Lai, and Hans Peter Graf · 2020
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Online multi-object tracking and segmentation with gmphd filter and simple affinity fusion
Young-min Song and Moongu Jeon · 2020
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What makes for good views for contrastive learning
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
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Unsupervised deep representation learning for real-time tracking
Ning Wang, Wengang Zhou, Yibing Song, Chao Ma, Wei Liu, and Houqiang Li · 2020
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Towards real-time multi-object tracking
Zhongdao Wang, Liang Zheng, Yixuan Liu, and Shengjin Wang · 2020
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Segment as points for efficient online multi-object tracking and segmentation
Zhenbo Xu, Wei Zhang, Xiao Tan, Wei Yang, Huan Huang, Shilei Wen, Errui Ding, and Liusheng Huang · 2020
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Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers
Chi Zhang, Yujun Cai, Guosheng Lin, and Chunhua Shen · 2020
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Fairmot: On the fairness of detection and re-identification in multiple object tracking
Yifu Zhang, Chunyu Wang, Xinggang Wang, Wenjun Zeng, and Wenyu Liu · 2020
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Towards accurate pixel-wise object tracking by attention retrieval
Zhipeng Zhang, Bing Li, Weiming Hu, and Houweng Peng · 2020
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Tracking objects as points
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Identity-guided human semantic parsing for person re-identification
Kuan Zhu, Haiyun Guo, Zhiwei Liu, Ming Tang, and Jinqiao Wang · 2020
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Motchallenge: A benchmark for single-camera multiple target tracking
Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian Reid, Stefan Roth, and Laura Leal-Taixé · 2021
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How well do self-supervised models transfer?
Linus Ericsson, Henry Gouk, and Timothy M Hospedales · 2021
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Cross-domain similarity learning for face recognition in unseen domains
Masoud Faraki, Xiang Yu, Yi-Hsuan Tsai, Yumin Suh, and Manmohan Chandraker · 2021
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Learning to track instances without video annotations
Yang Fu, Sifei Liu, Umar Iqbal, Shalini De Mello, Humphrey Shi, and Jan Kautz · 2021
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, Richard Socher, and Steven CH Hoi · 2021
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Fine-grained few-shot classification with feature map reconstruction networks
Davis Wertheimer, Luming Tang, and Bharath Hariharan · 2021
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Track to detect and segment: An online multi-object tracker
Jialian Wu, Jiale Cao, Liangchen Song, Yu Wang, Ming Yang, and Junsong Yuan · 2021
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Detco: Unsupervised contrastive learning for object detection
Enze Xie, Jian Ding, Wenhai Wang, Xiaohang Zhan, Hang Xu, Zhenguo Li, and Ping Luo · 2021
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Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning
Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, and Han Hu · 2021
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Rethinking self-supervised correspondence learning: A video frame-level similarity perspective
Jiarui Xu and Xiaolong Wang · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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