REU Program 2019 Week 3 Alex Ruiz Jyoti Kini Outline Weaksupervision based MultiObject Tracking Research Papers PyTorch Coding Exercise Experimental Qualitative Results Upcoming Schedule Weaksupervision based MultiObject Tracking ID: 768916
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REU Program 2019 Week 3 Alex Ruiz Jyoti Kini
OutlineWeak-supervision based Multi-Object Tracking Research PapersPyTorch Coding ExerciseExperimental Qualitative ResultsUpcoming Schedule
Weak-supervision based Multi-Object Tracking
Research Papers Neighbourhood Consensus Networks Simple Online and Realtime Tracking with Deep Association Metric
Neighbourhood Consensus Networks
Simple Online and Realtime Tracking with Deep Association Metric Reduces the number of identity switches with an association metric in which combines motion and appearance information Integrate the Matching Cascade Algorithm to decrease the uncertainty associated with the object location when occluding for a longer period of time
PyTorch Coding Exercise
Experimental Qualitative Results Key-point Matching Module for MOT
Upcoming Schedule
Thank You!
ReferencesRocco I, Cimpoi M, Arandjelović R, Torii A, Pajdla T, Sivic J. Neighbourhood Consensus Networks. InAdvances in Neural Information Processing Systems 2018 (pp. 1651-1662). Wojke N, Bewley A, Paulus D. Simple online and Realtime tracking with a deep association metric. In2017 IEEE International Conference on Image Processing (ICIP) 2017 Sep 17 (pp. 3645-3649). IEEE.