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Pose tracking is an important problem that requires identifying unique human pose-instances and matching them temporally across different frames of a video.
Pictorial structures for object recognition
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2005
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Measure locally, reason globally: Occlusion-sensitive articulated pose estimation
Leonid Sigal and Michael J Black · 2006
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Evaluating multiple object tracking performance: the clear mot metrics
Keni Bernardin and Rainer Stiefelhagen · 2008
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Multiple tree models for occlusion and spatial constraints in human pose estimation
Yang Wang and Greg Mori · 2008
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Pictorial structures revisited: People detection and articulated pose estimation
Mykhaylo Andriluka, Stefan Roth, and Bernt Schiele · 2009
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Human pose estimation using body parts dependent joint regressors
Matthias Dantone, Juergen Gall, Christian Leistner, and Luc Van Gool · 2013
Earlier work this paper cites.
2d human pose estimation - mpii human pose dataset
Mykhaylo Andriluka1, Leonid Pishchulin, Peter Gehler, and Bernt Schiele · 2014
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Very deep convolutional networks for large-scale image recognition, 2014
Karen Simonyan and Andrew Zisserman · 2014
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Deeppose: Human pose estimation via deep neural networks
Alexander Toshev and Christian Szegedy · 2014
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A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning · 2015
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Efficient object localization using convolutional networks
Jonathan Tompson, Ross Goroshin, Arjun Jain, Yann LeCun, and Christoph Bregler · 2015
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Ultra wideband indoor positioning technologies: Analysis and recent advances
Abdulrahman Alarifi, AbdulMalik Al-Salman, Mansour Alsaleh, Ahmad Alnafessah, Suheer Al-Hadhrami, Mai A Al-Ammar, and Hend S Al-Khalifa · 2016
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Modeling relationships in referential expressions with compositional modular networks
Ronghang Hu, Marcus Rohrbach, Jacob Andreas, Trevor Darrell, and Kate Saenko · 2016
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MOT16: A benchmark for multi-object tracking
Anton Milan, Laura Leal-Taixé, Ian D. Reid, Stefan Roth, and Konrad Schindler · 2016
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Convolutional pose machines
Shih-En Wei, Varun Ramakrishna, Takeo Kanade, and Yaser Sheikh · 2016
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Posetrack leaderboard, 2017 test set, 2017
2017
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Detecting visual relationships with deep relational networks
Bo Dai, Yuqi Zhang, and Dahua Lin · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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A coarse-fine network for keypoint localization
Shaoli Huang, Mingming Gong, and Dacheng Tao · 2017
Earlier work this paper cites.
Arttrack: Articulated multi-person tracking in the wild
Eldar Insafutdinov, Mykhaylo Andriluka, Leonid Pishchulin, Siyu Tang, Evgeny Levinkov, Bjoern Andres, and Bernt Schiele · 2017
Earlier work this paper cites.
Posetrack: Joint multi-person pose estimation and tracking
Umar Iqbal, Anton Milan, and Juergen Gall · 2017
Earlier work this paper cites.
Towards multi-person pose tracking: Bottom-up and top-down methods
Sheng Jin, Xujie Ma, Zhipeng Han, Yue Wu, Wei Yang, Wentao Liu, Chen Qian, and Wanli Ouyang · 2017
Earlier work this paper cites.
Towards accurate multi-person pose estimation in the wild
George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, and Kevin Murphy · 2017
Cited alongside, same era.
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David GT Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap · 2017
Cited alongside, same era.
Attention is all you need, 2017
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Joint multi-person pose estimation and semantic part segmentation
Fangting Xia, Peng Wang, Xianjie Chen, and Alan L Yuille · 2017
Cited alongside, same era.
Learning feature pyramids for human pose estimation
Wei Yang, Shuang Li, Wanli Ouyang, Hongsheng Li, and Xiaogang Wang · 2017
Cited alongside, same era.
Posetrack challenge - eccv 2018, 2018
2018
Video action transformer network
Rohit Girdhar, Joao Carreira, Carl Doersch, and Andrew Zisserman · 2019
Closest in time.
Multi-domain pose network for multi-person pose estimation and tracking
Hengkai Guo, Tang Tang, Guozhong Luo, Riwei Chen, Yongchen Lu, and Linfu Wen · 2019
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Dynamic graph modules for modeling object-object interactions in activity recognition: Supplementary material
Hao Huang, Luowei Zhou, Wei Zhang, Jason J Corso, and Chenliang Xu · 2019
Closest in time.
Pose estimator and tracker using temporal flow maps for limbs, 2019
Jihye Hwang, Jieun Lee, Sungheon Park, and Nojun Kwak · 2019
Closest in time.
Multi-person articulated tracking with spatial and temporal embeddings
Sheng Jin, Wentao Liu, Wanli Ouyang, and Chen Qian · 2019
Closest in time.
Visualbert: A simple and performant baseline for vision and language
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Cited alongside, same era.
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
Cited alongside, same era.
Cascaded pyramid network for multi-person pose estimation
Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, and Jian Sun · 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.
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.
Joint flow: Temporal flow fields for multi person tracking, 2018
Andreas Doering, Umar Iqbal, and Juergen Gall · 2018
Cited alongside, same era.
Learning to refine human pose estimation
Mihai Fieraru, Anna Khoreva, Leonid Pishchulin, and Bernt Schiele · 2018
Cited alongside, same era.
Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, and Kai-Wei Chang · 2019
Closest in time.
Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
Closest in time.
Posefix: Model-agnostic general human pose refinement network
Gyeongsik Moon, Ju Yong Chang, and Kyoung Mu Lee · 2019
Closest in time.
Lighttrack: A generic framework for online top-down human pose tracking
Guanghan Ning and Heng Huang · 2019
Closest in time.
A top-down approach to articulated human pose estimation and tracking
Guanghan Ning, Ping Liu, Xiaochuan Fan, and Chi Zhang · 2019
Closest in time.
Efficient online multi-person 2d pose tracking with recurrent spatio-temporal affinity fields
Yaadhav Raaj, Haroon Idrees, Gines Hidalgo, and Yaser Sheikh · 2019
Closest in time.
Stand-alone self-attention in vision models
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, and Jonathon Shlens · 2019
Closest in time.
Poinet: Pose-guided ovonic insight network for multi-person pose tracking
Weijian Ruan, Wu Liu, Qian Bao, Jun Chen, Yuhao Cheng, and Tao Mei · 2019
Closest in time.
Contrastive bidirectional transformer for temporal representation learning
Chen Sun, Fabien Baradel, Kevin Murphy, and Cordelia Schmid · 2019
Closest in time.
Deep high-resolution representation learning for human pose estimation
Ke Sun, Bin Xiao, Dong Liu, and Jingdong Wang · 2019
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Lxmert: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal · 2019
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pytorch-transformers, 2019
HuggingFace Team and Google AI Language Team · 2019
Closest in time.
Learning correspondence from the cycle-consistency of time
Xiaolong Wang, Allan Jabri, and Alexei A Efros · 2019
Closest in time.
Spatial-temporal relation networks for multi-object tracking
Jiarui Xu, Yue Cao, Zheng Zhang, and Han Hu · 2019
Closest in time.
Fastpose: Towards real-time pose estimation and tracking via scale-normalized multi-task networks, 2019
Jiabin Zhang, Zheng Zhu, Wei Zou, Peng Li, Yanwei Li, Hu Su, and Guan Huang · 2019
Closest in time.
Unified vision-language pre-training for image captioning and vqa
Luowei Zhou, Hamid Palangi, Lei Zhang, Houdong Hu, Jason J Corso, and Jianfeng Gao · 2019
Closest in time.