Anton Milan

Orcid: 0000-0002-9719-3616

Affiliations:
  • Amazon, Seattle, WA, USA
  • University of Adelaide, Australia (former)
  • University of Bonn, Germany (PhD 2013)


According to our database1, Anton Milan authored at least 35 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2022
Learn to Predict Sets Using Feed-Forward Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021
MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking.
Int. J. Comput. Vis., 2021

Multiple object tracking: A literature review.
Artif. Intell., 2021

2020
RefineNet: Multi-Path Refinement Networks for Dense Prediction.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

MOT20: A benchmark for multi object tracking in crowded scenes.
CoRR, 2020

Learn to Predict Sets Using Feed-Forward Neural Networks.
CoRR, 2020

2019
CVPR19 Tracking and Detection Challenge: How crowded can it get?
CoRR, 2019

2018
RGB-D object detection and semantic segmentation for autonomous manipulation in clutter.
Int. J. Robotics Res., 2018

Cartman: The Low-Cost Cartesian Manipulator that Won the Amazon Robotics Challenge.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018


PoseTrack: A Benchmark for Human Pose Estimation and Tracking.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Joint Learning of Set Cardinality and State Distribution.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Design of a Multi-Modal End-Effector and Grasping System: How Integrated Design helped win the Amazon Robotics Challenge.
CoRR, 2017

Cartman: Cartesian Manipulator for Warehouse Automation in Cluttered Environments.
CoRR, 2017

Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking.
CoRR, 2017

NimbRo picking: Versatile part handling for warehouse automation.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

DeepSetNet: Predicting Sets with Deep Neural Networks.
Proceedings of the IEEE International Conference on Computer Vision, 2017

RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

PoseTrack: Joint Multi-person Pose Estimation and Tracking.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Data-Driven Approximations to NP-Hard Problems.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Online Multi-Target Tracking Using Recurrent Neural Networks.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Multi-Target Tracking by Discrete-Continuous Energy Minimization.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

MOT16: A Benchmark for Multi-Object Tracking.
CoRR, 2016

Pose-Track: Joint Multi-Person Pose Estimation and Tracking.
CoRR, 2016

Joint Probabilistic Matching Using m-Best Solutions.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking.
CoRR, 2015

Joint Probabilistic Data Association Revisited.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Joint tracking and segmentation of multiple targets.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Continuous Energy Minimization for Multitarget Tracking.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Improving Global Multi-target Tracking with Local Updates.
Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

Privacy Preserving Multi-target Tracking.
Proceedings of the Computer Vision - ACCV 2014 Workshops, 2014

2013
Energy minimization for multiple object tracking.
PhD thesis, 2013

Learning People Detectors for Tracking in Crowded Scenes.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Challenges of Ground Truth Evaluation of Multi-target Tracking.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013

Detection- and Trajectory-Level Exclusion in Multiple Object Tracking.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013


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