MAT: Motion-Aware Multi-Object Tracking

[1]  Davide Modolo,et al.  SiamMOT: Siamese Multi-Object Tracking , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Zhenyu He,et al.  Adaptive ensemble perception tracking , 2021, Neural Networks.

[3]  Wongun Choi,et al.  Learning a Proposal Classifier for Multiple Object Tracking , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[4]  Chanho Kim,et al.  Discriminative Appearance Modeling with Multi-track Pooling for Real-time Multi-object Tracking , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Mathieu Salzmann,et al.  Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Zhenyu He,et al.  Self-Supervised Deep Correlation Tracking , 2020, IEEE Transactions on Image Processing.

[7]  Jian Wang,et al.  TPM: Multiple object tracking with tracklet-plane matching , 2020, Pattern Recognit..

[8]  Zhang Xiong,et al.  Multiplex Labeling Graph for Near-Online Tracking in Crowded Scenes , 2020, IEEE Internet of Things Journal.

[9]  Feiyue Huang,et al.  Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking , 2020, ECCV.

[10]  Bodo Rosenhahn,et al.  Lifted Disjoint Paths with Application in Multiple Object Tracking , 2020, ICML.

[11]  Ameya Prabhu,et al.  Simple Unsupervised Multi-Object Tracking , 2020, ArXiv.

[12]  Cewu Lu,et al.  TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Xinggang Wang,et al.  A Simple Baseline for Multi-Object Tracking , 2020, ArXiv.

[14]  Bin Liu,et al.  DASOT: A Unified Framework Integrating Data Association and Single Object Tracking for Online Multi-Object Tracking , 2020, AAAI.

[15]  Vladlen Koltun,et al.  Tracking Objects as Points , 2020, ECCV.

[16]  Ruigang Yang,et al.  A Unified Object Motion and Affinity Model for Online Multi-Object Tracking , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Xin Zhao,et al.  GlobalTrack: A Simple and Strong Baseline for Long-term Tracking , 2019, AAAI.

[18]  L. Leal-Taix'e,et al.  Learning a Neural Solver for Multiple Object Tracking , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Gang Yu,et al.  SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines , 2019, AAAI.

[20]  Shengjin Wang,et al.  Towards Real-Time Multi-Object Tracking , 2019, ECCV.

[21]  R. Horaud,et al.  How to Train Your Deep Multi-Object Tracker , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Ross B. Girshick,et al.  Mask R-CNN , 2017, 1703.06870.

[23]  Long Chen,et al.  Aggregate Tracklet Appearance Features for Multi-Object Tracking , 2019, IEEE Signal Processing Letters.

[24]  Bodo Rosenhahn,et al.  Multiple People Tracking Using Body and Joint Detections , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[25]  Xingyi Zhou,et al.  Objects as Points , 2019, ArXiv.

[26]  Haibin Ling,et al.  FAMNet: Joint Learning of Feature, Affinity and Multi-Dimensional Assignment for Online Multiple Object Tracking , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[27]  Laura Leal-Taixé,et al.  Tracking Without Bells and Whistles , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[28]  Wei Wu,et al.  Multi-Object Tracking with Multiple Cues and Switcher-Aware Classification , 2019, ArXiv.

[29]  Jenq-Neng Hwang,et al.  Exploit the Connectivity: Multi-Object Tracking with TrackletNet , 2018, ACM Multimedia.

[30]  Hua Yang,et al.  Online Multi-Object Tracking with Dual Matching Attention Networks , 2018, ECCV.

[31]  K. Madhava Krishna,et al.  Beyond Pixels: Leveraging Geometry and Shape Cues for Online Multi-Object Tracking , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[32]  Nuno Vasconcelos,et al.  Cascade R-CNN: Delving Into High Quality Object Detection , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[33]  Silvio Savarese,et al.  Recurrent Autoregressive Networks for Online Multi-object Tracking , 2017, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).

[34]  Yang Zhang,et al.  Enhancing Detection Model for Multiple Hypothesis Tracking , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[35]  Dietrich Paulus,et al.  Simple online and realtime tracking with a deep association metric , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[36]  Kaiming He,et al.  Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[37]  Ming-Hsuan Yang,et al.  Online Multi-object Tracking via Structural Constraint Event Aggregation , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[38]  Fan Yang,et al.  Exploit All the Layers: Fast and Accurate CNN Object Detector with Scale Dependent Pooling and Cascaded Rejection Classifiers , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[39]  Stefan Roth,et al.  MOT16: A Benchmark for Multi-Object Tracking , 2016, ArXiv.

[40]  Fabio Tozeto Ramos,et al.  Simple online and realtime tracking , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[41]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[42]  D. Tao,et al.  Connected Component Model for Multi-Object Tracking. , 2016, IEEE transactions on image processing : a publication of the IEEE Signal Processing Society.

[43]  James M. Rehg,et al.  Multiple Hypothesis Tracking Revisited , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[44]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[45]  Ming-Hsuan Yang,et al.  Bayesian Multi-object Tracking Using Motion Context from Multiple Objects , 2015, 2015 IEEE Winter Conference on Applications of Computer Vision.

[46]  S. Savarese,et al.  Learning an Image-Based Motion Context for Multiple People Tracking , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[47]  Pietro Perona,et al.  Microsoft COCO: Common Objects in Context , 2014, ECCV.

[48]  Ramakant Nevatia,et al.  Learning affinities and dependencies for multi-target tracking using a CRF model , 2011, CVPR 2011.

[49]  Silvio Savarese,et al.  Multiple Target Tracking in World Coordinate with Single, Minimally Calibrated Camera , 2010, ECCV.

[50]  Harold W. Kuhn,et al.  The Hungarian method for the assignment problem , 1955, 50 Years of Integer Programming.

[51]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[52]  Georgios D. Evangelidis,et al.  Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[53]  Rainer Stiefelhagen,et al.  Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics , 2008, EURASIP J. Image Video Process..

[54]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).