Dimity Miller

According to our database, Dimity Miller authored at least 21 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Electric Vehicle Next Charge Location Prediction.

Robert Marlin, Raja Jurdak, Alsharif Abuadbba, Sushmita Ruj, Dimity Miller

IEEE Trans. Intell. Transp. Syst., October, 2024

Open-Vocabulary Part-Based Grasping.

Tjeard van Oort, Dimity Miller, Will N. Browne, Nicolas Marticorena, Jesse Haviland, Niko Sünderhauf

CoRR, 2024

Open-Set Recognition in the Age of Vision-Language Models.

Dimity Miller, Niko Sünderhauf, Alex Kenna, Keita Mason

Proceedings of the Computer Vision - ECCV 2024, 2024

Unlearning Backdoor Attacks Through Gradient-Based Model Pruning.

Kealan Dunnett, Reza Arablouei, Dimity Miller, Volkan Dedeoglu, Raja Jurdak

Proceedings of the 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2024

Human and Large Language Model Intent Detection in Image-Based Self-Expression of People with Intellectual Disability.

Alieh Hajizadeh Saffar, Laurianne Sitbon, Maria Hoogstrate, Ahmed Abbas, Sirinthip Roomkham, Dimity Miller

Proceedings of the 2024 ACM SIGIR Conference on Human Information Interaction and Retrieval, 2024

2023

Addressing the Challenges of Open-World Object Detection.

David Pershouse, Feras Dayoub, Dimity Miller, Niko Sünderhauf

CoRR, 2023

Uncertainty-Aware Lidar Place Recognition in Novel Environments.

Keita Mason, Joshua Knights, Milad Ramezani, Peyman Moghadam, Dimity Miller

IROS, 2023

Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields.

Niko Sünderhauf, Jad Abou-Chakra, Dimity Miller

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Never mind the metrics - what about the uncertainty? Visualising binary confusion matrix metric distributions to put performance in perspective.

David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley

Proceedings of the International Conference on Machine Learning, 2023

SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection.

Samuel Wilson, Tobias Fischer, Feras Dayoub, Dimity Miller, Niko Sünderhauf

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Uncertainty for Identifying Open-Set Errors in Visual Object Detection.

Dimity Miller, Niko Sünderhauf, Michael Milford, Feras Dayoub

IEEE Robotics Autom. Lett., 2022

What's in the Black Box? The False Negative Mechanisms Inside Object Detectors.

Dimity Miller, Peyman Moghadam, Mark Cox, Matt Wildie, Raja Jurdak

IEEE Robotics Autom. Lett., 2022

Never mind the metrics - what about the uncertainty? Visualising confusion matrix metric distributions.

David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley

CoRR, 2022

Why Object Detectors Fail: Investigating the Influence of the Dataset.

Dimity Miller, Georgia Goode, Callum Bennie, Peyman Moghadam, Raja Jurdak

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Class Anchor Clustering: A Loss for Distance-based Open Set Recognition.

Dimity Miller, Niko Sünderhauf, Michael Milford, Feras Dayoub

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

2020

Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers.

Dimity Miller, Niko Sünderhauf, Michael Milford, Feras Dayoub

CoRR, 2020

Probabilistic Object Detection: Definition and Evaluation.

David Hall, Feras Dayoub, John Skinner, Haoyang Zhang, Dimity Miller, Peter Corke, Gustavo Carneiro, Anelia Angelova, Niko Sünderhauf

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Probabilistic Object Detection with an Ensemble of Experts.

Dimity Miller

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2019

Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection.

Dimity Miller, Feras Dayoub, Michael Milford, Niko Sünderhauf

Proceedings of the International Conference on Robotics and Automation, 2019

Benchmarking Sampling-based Probabilistic Object Detectors.

Dimity Miller, Niko Sünderhauf, Haoyang Zhang, David Hall, Feras Dayoub

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Dropout Sampling for Robust Object Detection in Open-Set Conditions.

Dimity Miller, Lachlan Nicholson, Feras Dayoub, Niko Sünderhauf

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018