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We present a novel transformer-based architecture for global multi-object tracking.
Multiple target tracking using spatio-temporal markov chain monte carlo data association
Qian Yu, Gérard Medioni, and Isaac Cohen · 2007
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Global data association for multi-object tracking using network flows
Li Zhang, Yuan Li, and Ramakant Nevatia · 2008
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Multiple object tracking using k-shortest paths optimization
Jerome Berclaz, Francois Fleuret, Engin Turetken, and Pascal Fua · 2011
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 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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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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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Simple online and realtime tracking
Alex Bewley, Zongyuan Ge, Lionel Ott, Fabio Ramos, and Ben Upcroft · 2016
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MOT16: A benchmark for multi-object tracking
A. Milan, L. Leal-Taixé, I. Reid, S. Roth, and K. Schindler · 2016
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Youtube-boundingboxes: A large high-precision human-annotated data set for object detection in video
Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, and Vincent Vanhoucke · 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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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End-to-end learning of multi-sensor 3D tracking by detection
Davi Frossard and Raquel Urtasun · 2018
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Crowdhuman: A benchmark for detecting human in a crowd
Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, and Jian Sun · 2018
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Deep cosine metric learning for person re-identification
Nicolai Wojke and Alex Bewley · 2018
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Deep layer aggregation
Fisher Yu, Dequan Wang, Evan Shelhamer, and Trevor Darrell · 2018
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Tracking without bells and whistles
Philipp Bergmann, Tim Meinhardt, and Laura Leal-Taixe · 2019
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Res2net: A new multi-scale backbone architecture
Shanghua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, and Philip HS Torr · 2019
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LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
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Got-10k: A large high-diversity benchmark for generic object tracking in the wild
Lianghua Huang, Xin Zhao, and Kaiqi Huang · 2019
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Bag of tricks and a strong baseline for deep person re-identification
Hao Luo, Youzhi Gu, Xingyu Liao, Shenqi Lai, and Wei Jiang · 2019
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FCOS: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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Long-term feature banks for detailed video understanding
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krahenbuhl, and Ross Girshick · 2019
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Sequence level semantics aggregation for video object detection
Haiping Wu, Yuntao Chen, Naiyan Wang, and Zhaoxiang Zhang · 2019
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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Exploring self-attention for image recognition
Hengshuang Zhao, Jiaya Jia, and Vladlen Koltun · 2020
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Tracking objects as points
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Transmot: Spatial-temporal graph transformer for multiple object tracking
Peng Chu, Jiang Wang, Quanzeng You, Haibin Ling, and Zicheng Liu · 2021
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Learning a proposal classifier for multiple object tracking
Peng Dai, Renliang Weng, Wongun Choi, Changshui Zhang, Zhangping He, and Wei Ding · 2021
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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
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Spatial-temporal relation networks for multi-object tracking
Jiarui Xu, Yue Cao, Zheng Zhang, and Han Hu · 2019
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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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Context r-cnn: Long term temporal context for per-camera object detection
Sara Beery, Guanhang Wu, Vivek Rathod, Ronny Votel, and Jonathan Huang · 2020
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Learning a neural solver for multiple object tracking
Guillem Brasó and Laura Leal-Taixé · 2020
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2021
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1st place solution to ECCV-TAO-2020: Detect and represent any object for tracking
Fei Du, Bo Xu, Jiasheng Tang, Yuqi Zhang, Fan Wang, and Hao Li · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Group-free 3D object detection via transformers
Ze Liu, Zheng Zhang, Yue Cao, Han Hu, and Xin Tong · 2021
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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 · 2021
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Quasi-dense similarity learning for multiple object tracking
Jiangmiao Pang, Linlu Qiu, Xia Li, Haofeng Chen, Qi Li, Trevor Darrell, and Fisher Yu · 2021
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Sparse r-cnn: End-to-end object detection with learnable proposals
Peize Sun, Rufeng Zhang, Yi Jiang, Tao Kong, Chenfeng Xu, Wei Zhan, Masayoshi Tomizuka, Lei Li, Zehuan Yuan, Changhu Wang, et al · 2021
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Learning to track with object permanence
Pavel Tokmakov, Jie Li, Wolfram Burgard, and Adrien Gaidon · 2021
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Multiple object tracking with correlation learning
Qiang Wang, Yun Zheng, Pan Pan, and Yinghui Xu · 2021
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Unidentified video objects: A benchmark for dense, open-world segmentation
Weiyao Wang, Matt Feiszli, Heng Wang, and Du Tran · 2021
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Joint object detection and multi-object tracking with graph neural networks
Yongxin Wang, Kris Kitani, and Xinshuo Weng · 2021
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End-to-end video instance segmentation with transformers
Yuqing Wang, Zhaoliang Xu, Xinlong Wang, Chunhua Shen, Baoshan Cheng, Hao Shen, and Huaxia Xia · 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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Transcenter: Transformers with dense queries for multiple-object tracking
Yihong Xu, Yutong Ban, Guillaume Delorme, Chuang Gan, Daniela Rus, and Xavier Alameda-Pineda · 2021
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End-to-end multiple-object tracking with transformer
Fangao Zeng, Bin Dong, Tiancai Wang, Cheng Chen, Xiangyu Zhang, and Yichen Wei · 2021
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Probabilistic two-stage detection
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2021
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Looking beyond two frames: End-to-end multi-object tracking using spatial and temporal transformers
Tianyu Zhu, Markus Hiller, Mahsa Ehsanpour, Rongkai Ma, Tom Drummond, and Hamid Rezatofighi · 2021
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
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