| 2026 | WACV | Intra-Class Probabilistic Embeddings for Uncertainty Estimation in Vision-Language Models. | Zhenxiang Lin, Maryam Haghighat, Will Browne, Dimity Miller |
| 2025 | CVPR | Multi-View Pose-Agnostic Change Localization with Zero Labels. | Chamuditha Jayanga Galappaththige, Jason Lai, Lloyd Windrim, Donald G. Dansereau, Niko Snderhauf, Dimity Miller |
| 2024 | CHIIR | 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 |
| 2024 | DSN | Unlearning Backdoor Attacks Through Gradient-Based Model Pruning. | Kealan Dunnett, Reza Arablouei, Dimity Miller, Volkan Dedeoglu, Raja Jurdak |
| 2024 | ECCV | Open-Set Recognition in the Age of Vision-Language Models. | Dimity Miller, Niko Snderhauf, Alex Kenna, Keita Mason |
| 2023 | ICCV | SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection. | Samuel Wilson, Tobias Fischer, Feras Dayoub, Dimity Miller, Niko Snderhauf |
| 2023 | ICML | 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 |
| 2023 | IROS | Uncertainty-Aware Lidar Place Recognition in Novel Environments. | Keita Mason, Joshua Knights, Milad Ramezani, Peyman Moghadam, Dimity Miller |
| 2023 | ICRA | Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields. | Niko Snderhauf, Jad Abou-Chakra, Dimity Miller |
| 2022 | CVPR | Why Object Detectors Fail: Investigating the Influence of the Dataset. | Dimity Miller, Georgia Goode, Callum Bennie, Peyman Moghadam, Raja Jurdak |
| 2021 | WACV | Class Anchor Clustering: A Loss for Distance-based Open Set Recognition. | Dimity Miller, Niko Snderhauf, Michael Milford, Feras Dayoub |
| 2020 | ECCV | Probabilistic Object Detection with an Ensemble of Experts. | Dimity Miller |
| 2020 | WACV | Probabilistic Object Detection: Definition and Evaluation. | David Hall, Feras Dayoub, John Skinner, Haoyang Zhang, Dimity Miller, Peter Corke, Gustavo Carneiro, Anelia Angelova, Niko Snderhauf |
| 2019 | CVPR | Benchmarking Sampling-based Probabilistic Object Detectors. | Dimity Miller, Niko Snderhauf, Haoyang Zhang, David Hall, Feras Dayoub |
| 2019 | ICRA | Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection. | Dimity Miller, Feras Dayoub, Michael Milford, Niko Snderhauf |
| 2018 | ICRA | Dropout Sampling for Robust Object Detection in Open-Set Conditions. | Dimity Miller, Lachlan Nicholson, Feras Dayoub, Niko Snderhauf |