Zhe Chen
Orcid: 0000-0001-5004-8975Affiliations:
- University of Sydney, School of Computer ScienceNSW, Australia (PhD 2019)
- University of Technology Sydney, Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, NSW, Australia (PhD 2017)
According to our database1,
Zhe Chen
authored at least 30 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
IEEE Trans. Cybern., March, 2024
2023
Transformer-Based Context Condensation for Boosting Feature Pyramids in Object Detection.
Int. J. Comput. Vis., October, 2023
Pattern Recognit., June, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-Based Beam Search.
IEEE Trans. Image Process., 2022
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search.
CoRR, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
IEEE Trans. Circuits Syst. Video Technol., 2021
Terra: A Smart and Sensible Digital Twin Framework for Robust Robot Deployment in Challenging Environments.
IEEE Internet Things J., 2021
A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection.
Int. J. Comput. Vis., 2021
CoRR, 2021
2020
IEEE Trans. Image Process., 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
2019
2018
Proceedings of the Computer Vision - ECCV 2018, 2018
2017
Proceedings of the Neural Information Processing - 24th International Conference, 2017
Proceedings of the Neural Information Processing - 24th International Conference, 2017
2015
MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015