Browse By Person: Zhang, Haoyang
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Number of items: 10.
2022
Hall, David, Talbot, Ben, Bista, Suman Raj, Zhang, Haoyang, Smith, Rohan, Dayoub, Feras, & Sünderhauf, Niko
(2022)
BenchBot environments for active robotics (BEAR): Simulated data for active scene understanding research.
International Journal of Robotics Research, 41(3), pp. 259-269.
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2021
Bista, Suman Raj, Hall, David, Talbot, Ben, Zhang, Haoyang, Dayoub, Feras, & Sunderhauf, Niko
(2021)
Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM.
In
Proceedings of the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 5328-5335.
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Zhang, Haoyang, Wang, Ying, Dayoub, Feras, & Sünderhauf, Niko
(2021)
VarifocalNet: An IoU-aware Dense Object Detector.
In
Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Institute of Electrical and Electronics Engineers (IEEE), United States of America, pp. 8510-8519.
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2020
Hall, D., Dayoub, F., Skinner, J., Zhang, H., Miller, D., Corke, P., Carneiro, G., Angelova, A., & Sünderhauf, N.
(2020)
Probabilistic object detection: Definition and evaluation.
In
Proceedings of the 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).
Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 1020-1029.
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2019
Suenderhauf, Niko, Dayoub, Feras, Hall, David, Skinner, John, Zhang, Haoyang, Carneiro, Gustavo, & Corke, Peter
(2019)
A probabilistic challenge for object detection.
Nature Machine Intelligence, 1(9), p. 443.
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Miller, Dimity, Suenderhauf, Niko, Zhang, Haoyang, Hall, David, & Dayoub, Feras
(2019)
Benchmarking sampling-based probabilistic object detectors.
In
Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 42-45.
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2017
Zhang, Haoyang & He, Xuming
(2017)
Deep free-form deformation network for object-mask registration.
In
Sebe, N, Soatto, S, Cucchiara, R, & Matsushita, Y (Eds.) Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV 2017).
Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 4261-4269.
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Zhang, Haoyang, He, Xuming, & Porikli, Fatih
(2017)
Learning spatial transforms for refining object segment proposals.
In
Turk, M, Brown, M S, Feris, R, & Sanderson, C (Eds.) Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision (WACV 2017).
Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 37-46.
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Zhang, Haoyang, He, Xuming, & Porikli, Fatih
(2017)
Learning to generate object segment proposals with multi-modal cues.
In
Lai, S H, Sato, Y, Lepetit, V, & Nishino, K (Eds.) Computer Vision - ACCV 2016: 13th Asian Conference on Computer Vision, Revised Selected Papers, Part I (Lecture Notes in Computer Science, Volume 10111).
Springer, Switzerland, pp. 121-136.
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2016
Zhang, Haoyang, He, Xuming, Porikli, Fatih, & Kneip, Laurent
(2016)
Semantic context and depth-aware object proposal generation.
In
Sharma, G & Pereira, F (Eds.) Proceedings of the 23rd IEEE International Conference on Image Processing (ICIP).
Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 1-5.
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