The paper list for Multi-Object-Tracking (Heavily borrowed from: multi-object-tracking-paper-list)
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MOT16: A Benchmark for Multi-Object Tracking, Milan, Anton, Laura Leal-Taixé, Ian Reid, Stefan Roth, and Konrad Schindler. arXiv preprint arXiv:1603.00831 (2016). Paper, Dataset
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MOT-2017 benchmark, Project
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Vision meets drones: a challenge, Zhu, Pengfei, Longyin Wen, Xiao Bian, Haibin Ling, and Qinghua Hu. arXiv preprint arXiv:1804.07437 (2018).
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"MOTS: Multi-Object Tracking and Segmentation" CVPR-2019. Voigtlaender, Paul, Michael Krause, Aljosa Osep, Jonathon Luiten, Berin Balachandar Gnana Sekar, Andreas Geiger, and Bastian Leibe. Paper
- Matlab: https://bitbucket.org/amilan/motchallenge-devkit/src/default/
- Python: https://github.com/cheind/py-motmetrics
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Multiple object tracking: A literature review arXiv preprint arXiv:1409.7618 (2014). Luo, Wenhan, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Xiaowei Zhao, and Tae-Kyun Kim.
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Machine learning methods for solving assignment problems in multi-target tracking. arXiv preprint arXiv:1802.06897 (2018). Emami, Patrick, Panos M. Pardalos, Lily Elefteriadou, and Sanjay Ranka.
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Slides: Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects, Hamed Pirsiavash, Deva Ramanan, and Charless C. Fowlkes University of California, Irvine, April 29, 2015
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DEEP LEARNING IN VIDEO MULTI-OBJECT TRACKING: A SURVEY, Gioele Ciaparrone, Francisco Luque Sánchez, Siham Tabik, Luigi Troiano, Roberto Tagliaferri, Francisco Herrera,[arXiv]
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Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers He, Zhen, Jian Li, Daxue Liu, Hangen He, and David Barber. Code, CVPR-2019
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Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics. Meirovitch, Yaron, Lu Mi, Hayk Saribekyan, Alexander Matveev, David Rolnick, Casimir Wierzynski, and Nir Shavit, CVPR-2019
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DeepMOT: A Differentiable Framework for Training Multiple Object Trackers, Yihong Xu, Yutong Ban, Xavier Alameda-Pineda, Radu Horaud, arXiv 2019, Paper, GitHub
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Tracking without bells and whistles, Philipp Bergmann, Tim Meinhardt, Laura Leal-Taixe, Paper, GitHub
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Multi-Object Tracking with Multiple Cues and Switcher-Aware Classification, Feng, Weitao, Zhihao Hu, Wei Wu, Junjie Yan, and Wanli Ouyang, arXiv:1901.06129 (2019), Paper
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Learning Non-Uniform Hypergraph for Multi-Object Tracking, Wen, Longyin, Dawei Du, Shengkun Li, Xiao Bian, and Siwei Lyu, arXiv:1812.03621 (2018). Paper.
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End-to-End Learning Deep CRF models for Multi-Object Tracking, Jun Xiang, Chao Ma, Guohan Xu, Jianhua Hou, arXiv [paper]
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End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning, Fabian B. Fuchs, Adam R. Kosiorek, Li Sun, Oiwi Parker Jones, Ingmar Posner, [arXiv]
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Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management, Young-min Song, Kwangjin Yoon, Young-Chul Yoon, Kin-Choong Yow, Moongu Jeon, [Paper]
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Online Multi-Object Tracking with Dual Matching Attention Networks" Zhu, Ji and Yang, Hua and Liu, Nian and Kim, Minyoung and Zhang, Wenjun and Yang, Ming-Hsuan, ECCV-2018. Github
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Collaborative Deep Reinforcement Learning for Multi-Object Tracking Ren, Liangliang and Lu, Jiwen and Wang, Zifeng and Tian, Qi and Zhou, Jie, ECCV-2018.
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Multi-object Tracking with Neural Gating Using Bilinear LSTM Kim, Chanho and Li, Fuxin and Rehg, James M, ECCV-2018.
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A prior-less method for multi-face tracking in unconstrained videos Lin, Chung-Ching, and Ying Hung. CVPR-2018.
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Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World Fabbri, Matteo, Fabio Lanzi, Simone Calderara, Andrea Palazzi, Roberto Vezzani, and Rita Cucchiara, ECCV-2018, Project-page, Github.
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Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-identification, Long Chen, Haizhou Ai, Zijie Zhuang, Chong Shang, Paper, Code