多目标跟踪论文汇总（2021年 MOT paper）
arXiv 2021
ByteTrack: Multi-Object Tracking by Associating Every Detection Box (arXiv 2021-10)
Yifu Zhang, Peize Sun, Yi Jiang, Dongdong Yu, Zehuan Yuan, Ping Luo, Wenyu Liu, Xinggang Wang.
[paper][code]
One More Check: Making “Fake Background” Be Tracked Again. (arXiv 2021-4)
Chao Liang, Zhipeng Zhang, Xue Zhou, Bing Li, Yi Lu, Weiming Hu.
[paper] [code]
DEFT: Detection Embeddings for Tracking. (arXiv 2021-2)
Mohamed Chaabane, Peter Zhang, J. Ross Beveridge, Stephen O’Hara.
[paper] [code]
MOTR: End-to-End Multiple-Object Tracking with TRansformer. (arXiv 2021-5-7)
Fangao Zeng*, Bin Dong*, Tiancai Wang*, Cheng Chen, Xiangyu Zhang, Yichen Wei.
[paper] [code]
TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Tracking. (arXiv 2021-1)
Akshay Rangesh, Pranav Maheshwari, Mez Gebre, Siddhesh Mhatre, Vahid Ramezani, Mohan M. Trivedi.
[paper] [code]
TrackFormer: Multi-Object Tracking with Transformers. (arXiv 2021-1)
Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixe, Christoph Feichtenhofer.
[paper] [code]
Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking. (arXiv 2021-3)
Xuewu Lin, Yu-ang Guo, Jianqiang Wang.
[paper]
RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation. (arXiv 2021-5)
En Yu, Zhuoling Li, Shoudong Han, Hongwei Wang
[paper]
TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking. (arXiv 2021-4-1)
Peng Chu, Jiang Wang, Quanzeng You, Haibin Ling, Zicheng Liu.
[paper]
TransCenter: Transformers with Dense Queries for Multiple-Object Tracking. (arXiv 2021-3)
Yihong Xu, Yutong Ban, Guillaume Delorme, Chuang Gan, Daniela Rus, Xavier Alameda-Pineda.
[paper]
NeurIPS 2021
Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation. (NeurIPS 2021)
Pavel Tokmakov, Jie Li, Wolfram Burgard, Adrien Gaidon.
[paper] [code]
Self-Supervised Multi-Object Tracking with Cross-input Consistency. (NeurIPS 2021)
Favyen Bastani, Songtao He, Samuel Madden.
[paper] [code]
Do Different Tracking Tasks Require Different Appearance Models? (NeurIPS 2021)
Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip Torr, Luca Bertinetto.
[paper] [code]
ICCV 2021
Learning to Track with Object Permanence (ICCV 2021)
Pavel Tokmakov, Jie Li, Wolfram Burgard, Adrien Gaidon
[paper]
Assignment-Space-Based Multi-Object Tracking and Segmentation. (ICCV 2021)
Anwesa Choudhuri, Girish Chowdhary, Alexander G. Schwing
[paper]
A General Recurrent Tracking Framework Without Real Data. (ICCV 2021)
Shuai Wang, Hao Sheng, Yang Zhang, Yubin Wu, Zhang Xiong
[paper]
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving. (ICCV 2021)
Chenxu Luo, Xiaodong Yang, Alan Yuille
[paper] [code]
Track Without Appearance: Learn Box and Tracklet Embedding With Local and Global Motion Patterns for Vehicle Tracking. (ICCV 2021)
Gaoang Wang, Renshu Gu, Zuozhu Liu, Weijie Hu, Mingli Song, Jenq-Neng Hwang
[paper] [code]
Continuous Copy-Paste for One-Stage Multi-Object Tracking and Segmentation. (ICCV 2021)
Zhenbo Xu, Ajin Meng, Zhenbo Shi, Wei Yang, Zhi Chen, Liusheng Huang
[paper] [code]
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?. (ICCV 2021)
Zhenbo Xu, Ajin Meng, Zhenbo Shi, Wei Yang, Zhi Chen, Liusheng Huang
[paper]
CVPR 2021
Discriminative Appearance Modeling With Multi-Track Pooling for Real-Time Multi-Object Tracking. (CVPR 2021)
Chanho Kim, Li Fuxin, Mazen Alotaibi, James M. Rehg.
[paper] [code]
DyGLIP: A Dynamic Graph Model With Link Prediction for Accurate Multi-Camera Multiple Object Tracking. (CVPR 2021)
Kha Gia Quach, Pha Nguyen, Huu Le, Thanh-Dat Truong, Chi Nhan Duong, Minh-Triet Tran, Khoa Luu.
[paper] [code]
GMOT-40: A Benchmark for Generic Multiple Object Tracking. (CVPR 2021)
Hexin Bai, Wensheng Cheng, Peng Chu, Juehuan Liu, Kai Zhang, Haibin Ling.
[paper] [code]
Learning a Proposal Classifier for Multiple Object Tracking. (CVPR 2021)
Peng Dai, Renliang Weng, Wongun Choi, Changshui Zhang, Zhangping He, Wei Ding.
[paper] [code]
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking. (CVPR 2021)
Jiawei He, Zehao Huang, Naiyan Wang, Zhaoxiang Zhang.
[paper]
Multiple Object Tracking with Correlation Learning. (CVPR 2021)
Qiang Wang, Yun Zheng, Pan Pan, Yinghui Xu.
[paper]
Online Multiple Object Tracking with Cross-Task Synergy. (CVPR 2021)
Song Guo, Jingya Wang, Xinchao Wang, Dacheng Tao.
[paper] [code]
Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking. (CVPR 2021)
Fatemeh Saleh, Sadegh Aliakbarian, Hamid Rezatofighi, Mathieu Salzmann, Stephen Gould.
[paper]
Quasi-Dense Similarity Learning for Multiple Object Tracking. (CVPR 2021)
Jiangmiao Pang, Linlu Qiu, Xia Li, Haofeng Chen, Qi Li, Trevor Darrell, Fisher Yu.
[paper] [code]
SiamMOT: Siamese Multi-Object Tracking. (CVPR 2021)
Bing Shuai, Andrew Berneshawi, Xinyu Li, Davide Modolo, Joseph Tighe.
[paper]
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge. (CVPR 2021)
Francisco Rivera Valverde, Juana Valeria Hurtado, Abhinav Valada.
[paper] [code]
Track to Detect and Segment: An Online Multi-Object Tracker. (CVPR 2021)
Jialian Wu, Jiale Cao, Liangchen Song, Yu Wang, Ming Yang, Junsong Yuan.
[paper][code]
Track, Check, Repeat: An EM Approach to Unsupervised Tracking. (CVPR 2021)
Adam W. Harley, Yiming Zuo, Jing Wen, Ayush Mangal, Shubhankar Potdar, Ritwick Chaudhry, Katerina Fragkiadaki.
[paper]
Improving Multiple Pedestrian Tracking by Track Management and Occlusion Handling. (CVPR 2021)
Daniel Stadler, Jurgen Beyerer
[paper]
Improving Multiple Object Tracking With Single Object Tracking
Linyu Zheng, Ming Tang, Yingying Chen, Guibo Zhu, Jinqiao Wang, Hanqing Lu
[paper]
Polygonal Point Set Tracking
Gunhee Nam, Miran Heo, Seoung Wug Oh, Joon-Young Lee, Seon Joo Kim
[paper]
Seeing Behind Objects for 3D Multi-Object Tracking in RGB-D Sequences
Norman Muller, Yu-Shiang Wong, Niloy J. Mitra, Angela Dai, Matthias Niessner
[paper]
Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark
Longyin Wen, Dawei Du, Pengfei Zhu, Qinghua Hu, Qilong Wang, Liefeng Bo, Siwei Lyu
[paper]
整理不易，会有缺失，望提醒。谢谢！