Dimity Miller
Dimity Miller
Queensland University of Technology, Australian Centre for Robotic Vision
Verified email at hdr.qut.edu.au
Title
Cited by
Cited by
Year
Dropout sampling for robust object detection in open-set conditions
D Miller, L Nicholson, F Dayoub, N Sünderhauf
2018 IEEE International Conference on Robotics and Automation (ICRA), 3243-3249, 2018
772018
Probabilistic object detection: Definition and evaluation
D Hall, F Dayoub, J Skinner, H Zhang, D Miller, P Corke, G Carneiro, ...
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
412020
Evaluating merging strategies for sampling-based uncertainty techniques in object detection
D Miller, F Dayoub, M Milford, N Sünderhauf
2019 International Conference on Robotics and Automation (ICRA), 2348-2354, 2019
342019
Benchmarking Sampling-based Probabilistic Object Detectors.
D Miller, N Sünderhauf, H Zhang, D Hall, F Dayoub
CVPR Workshops 3, 6, 2019
82019
Class anchor clustering: A loss for distance-based open set recognition
D Miller, N Sunderhauf, M Milford, F Dayoub
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
5*2021
Uncertainty for Identifying Open-Set Errors in Visual Object Detection
D Miller, N Sünderhauf, M Milford, F Dayoub
arXiv preprint arXiv:2104.01328, 2021
2021
Probabilistic Object Detection with an Ensemble of Experts
D Miller
European Conference on Computer Vision, 46-55, 2020
2020
Probabilistic Object Detection: Definition and Evaluation-supplementary material
D Hall, F Dayoub, J Skinner, H Zhang, D Miller, P Corke, G Carneiro, ...
Dropout Variational Inference Improves Object Detection in Open-Set Conditions
D Miller, L Nicholson, F Dayoub, N Sünderhauf
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Articles 1–9