Research Interests
Computer Vision Knowledge Representation and Machine Learning Robotics and AutomationAPrf Feras Dayoub
Associate Professor
School of Computer Science and Information Technology
College of Engineering and Information Technology
I work at the intersection of computer vision, machine learning, and robotics, specializing in Embodied AI and Robotic Vision as part of the Australian Institute for Machine Learning (AIML) at Adelaide University. I lead the Embodied AI and Robotic Vision Group and serve as Deputy Director of the French–Australian CROSSING Lab (CNRS IRL), where we advance research in human–autonomous teaming and the development of intelligent, adaptive robotic systems. My research focuses on enabling robust perception, learning, and decision-making for real-world embodied agents, bridging foundational advances in AI with deployment in complex, dynamic environments.
My Overarching Research Question:
How can machine learning empower robots to better understand and interact with the world?
Research Group
Embodied AI and Robotic Vision Research Group
Research Themes
Embodied AI, Vision–Language-Action Models, and Foundation Models for Robotic Autonomy
This research theme explores how large language models, vision-language models, and foundation models can be integrated into robotic systems to support open-vocabulary reasoning, zero-shot navigation, execution monitoring, and language-guided physical interaction. Our work in this area focuses on making these models useful for embodied agents operating in open and dynamic environments, while improving their adaptability, interpretability, and robustness during deployment.
Selected paper
- KITE: Keyframe-Indexed Tokenized Evidence for VLM-Based Robot Failure Analysis — ICRA 2026
- SmartWay: Enhanced Waypoint Prediction and Backtracking for Zero-Shot Vision-and-Language Navigation — IROS 2025
- To Ask or Not to Ask? Detecting Absence of Information in Vision and Language Navigation — WACV 2025
- QueryAdapter: Rapid Adaptation of Vision-Language Models in Response to Natural Language Queries — IROS 2025
- 3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer — CVPR 2025
- ObjectReact: Learning Object-Relative Control for Visual Navigation — CoRL 2025
- TANGO: Traversability-Aware Navigation with Local Metric Control for Topological Goals — ICRA 2025
- RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation — ICRA 2024
Reliable, Adaptive, and Open-World Robotic Perception
This theme focuses on reliable perception under uncertainty. We develop methods for open-world object detection, unknown-class recognition, and out-of-distribution detection so that robotic systems can identify novel objects, recognise when inputs fall outside training assumptions, and behave more safely in unstructured real-world environments. This line of research contributes to trustworthy robotic perception beyond conventional closed-set accuracy benchmarks.
Selected paper
- SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection — ICCV 2023
- Hyperdimensional Feature Fusion for Out-of-Distribution Detection — WACV 2023
- Dropout sampling for robust object detection in open-set conditions - ICRA 2018
- Class anchor clustering: A loss for distance-based open set recognition - WACV 2021
- Uncertainty for identifying open-set errors in visual object detection- IEEE RAL 2022
- Embodied Domain Adaptation for Object Detection — IROS 2025
- Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection — IEEE RAL 2023
Cross-View Localization and Scene Change Detection
This area investigates long-term localisation and map maintenance using cross-view reasoning, multi-view temporal information, and foundation-model features. Our work in this space includes ground-to-aerial localisation, sequential cross-view localisation, scene change detection, and city-scale HD map updating. Together, these contributions support robust localisation and environmental understanding in dynamic, large-scale, and partially changing environments.
Selected paper
- SceneEdited: A City-Scale Benchmark for 3D HD Map Updating via Image-Guided Change Detection — WACV 2026
- Robust Scene Change Detection Using Visual Foundation Models and Cross-Attention Mechanisms — ICRA 2025
- Cross-Attention Between Satellite and Ground Views for Enhanced Fine-Grained Robot Geo-Localization — WACV 2024
- Temporal Attention for Cross-View Sequential Image Localization — IROS 2024
| Date | Position | Institution name |
|---|---|---|
| 2026 - ongoing | Associate Professor | Adelaide University |
| 2022 - 2025 | Senior Lecturer | University of Adelaide |
| 2022 - 2025 | Adjunct Senior Lecturer | Queensland University of Technology |
| 2019 - 2022 | Senior Lecturer | Queensland University of Technology |
| 2016 - 2019 | Centre Research Fellow | Center for Excellence in Robotic Robotics Vision (ACRV) |
| 2012 - 2016 | Postdoctoral Research Fellow | Queensland University of Technology |
| Year | Citation |
|---|---|
| 2025 | Cocks, S. L., Dreo, S., & Dayoub, F. (2025). AIMC-Spec: A Benchmark Dataset for Automatic Intrapulse Modulation Classification under Variable Noise Conditions. IEEE Access, 13, 1. |
| 2023 | Pershouse, D., Dayoub, F., Miller, D., & Sünderhauf, N. (2023). Addressing the Challenges of Open-World Object Detection. |
| 2023 | Shi, X., Qiao, Y., Wu, Q., Liu, L., & Dayoub, F. (2023). Improving Online Source-free Domain Adaptation for Object Detection by Unsupervised Data Acquisition. |
| 2023 | Chapman, N. H., Dayoub, F., Browne, W., & Lehnert, C. (2023). Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection. IEEE Robotics and Automation Letters, 8(8), 1-8. Scopus9 WoS5 |
| 2022 | Hall, D., Talbot, B., Bista, S. R., Zhang, H., Smith, R., Dayoub, F., & Sünderhauf, N. (2022). BenchBot environments for active robotics (BEAR): Simulated data for active scene understanding research. International Journal of Robotics Research, 41(3), 259-269. Scopus4 WoS4 |
| 2022 | Rahman, Q. M., Sunderhauf, N., Corke, P., & Dayoub, F. (2022). FSNet: A Failure Detection Framework for Semantic Segmentation. IEEE Robotics and Automation Letters, 7(2), 1-8. Scopus17 WoS17 |
| 2022 | Miller, D., Sunderhauf, N., Milford, M., & Dayoub, F. (2022). Uncertainty for identifying open-set errors in visual object detection. IEEE Robotics and Automation Letters, 7(1), 215-222. Scopus43 WoS33 |
| 2021 | Talbot, B., Dayoub, F., Corke, P., & Wyeth, G. (2021). Robot navigation in unseen spaces using an abstract map. IEEE Transactions on Cognitive and Developmental Systems, 13(4), 791-805. Scopus18 WoS14 |
| 2021 | Rahman, Q. M., Corke, P., & Dayoub, F. (2021). Run-time monitoring of machine learning for robotic perception: a survey of emerging trends. IEEE Access, 9, 20067-20075. Scopus58 WoS50 |
| 2020 | Haviland, J., Dayoub, F., & Corke, P. (2020). Control of the Final-Phase of Closed-Loop Visual Grasping using Image-Based Visual Servoing. |
| 2020 | Arain, B., Dayoub, F., Rigby, P., & Dunbabin, M. (2020). Close-Proximity Underwater Terrain Mapping Using Learning-based Coarse Range Estimation. |
| 2019 | Skinner, J., Hall, D., Zhang, H., Dayoub, F., & Sünderhauf, N. (2019). The Probabilistic Object Detection Challenge. |
| 2019 | Sünderhauf, N., Dayoub, F., Hall, D., Skinner, J., Zhang, H., Carneiro, G., & Corke, P. (2019). A probabilistic challenge for object detection. Nature Machine Intelligence, 1(9), 443. WoS3 |
| 2018 | Ahn, H. S., Sa, I., & Dayoub, F. (2018). Introduction to the Special Issue on Precision Agricultural Robotics and Autonomous Farming Technologies. IEEE Robotics and Automation Letters, 3(4), 4435-4438. Scopus5 WoS3 |
| 2018 | Hall, D., Dayoub, F., Perez, T., & McCool, C. (2018). A rapidly deployable classification system using visual data for the application of precision weed management. Computers and Electronics in Agriculture, 148, 107-120. Scopus22 WoS16 Europe PMC2 |
| 2017 | Bawden, O., Kulk, J., Russell, R., McCool, C., English, A., Dayoub, F., . . . Perez, T. (2017). Robot for weed species plant-specific management. Journal of Field Robotics, 34(6), 1179-1199. Scopus185 WoS154 |
| 2017 | Sa, I., Lehnert, C., English, A., McCool, C., Dayoub, F., Upcroft, B., & Perez, T. (2017). Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting-Combined Color and 3-D Information. IEEE Robotics and Automation Letters, 2(2), 765-772. Scopus114 WoS95 |
| 2016 | Sa, I., Ge, Z., Dayoub, F., Upcroft, B., Perez, T., & McCool, C. (2016). Deepfruits: A fruit detection system using deep neural networks. Sensors (Switzerland), 16(8), 1-23. Scopus1050 WoS763 Europe PMC225 |
| 2015 | Dayoub, F., Morris, T., & Corke, P. (2015). Rubbing shoulders with mobile service robots. IEEE Access, 3, 333-342. Scopus8 WoS8 |
| 2011 | Dayoub, F., Cielniak, G., & Duckett, T. (2011). Long-term experiments with an adaptive spherical view representation for navigation in changing environments. Robotics and Autonomous Systems, 59(5), 285-295. Scopus50 WoS42 |
| - | Clement, B., Dubromel, M., Santos, P. E., Sammut, K., Oppert, M., & Dayoub, F. (2024). Hybrid Navigation Acceptability and Safety. Proceedings of the AAAI Symposium Series, 2(1), 11-17. |
| Year | Citation |
|---|---|
| 2020 | Garg, S., Sünderhauf, N., Dayoub, F., Morrison, D., Cosgun, A., Carneiro, G., . . . Milford, M. (2020). Semantics for Robotic Mapping, Perception and Interaction: A Survey (Vol. 8). United States: Now Publishers. DOI |
| Year | Citation |
|---|---|
| 2025 | Shi, X., Qiao, Y., Wu, Q., Liu, L., & Dayoub, F. (2025). Improving Online Source-Free Domain Adaptation for Object Detection by Unsupervised Data Acquisition. In A. DelBue, C. Canton, J. Pont-Tuset, & T. Tommasi (Eds.), Lecture Notes in Computer Science (Vol. 15629 LNCS, pp. 195-205). SPRINGER INTERNATIONAL PUBLISHING AG. DOI Scopus2 WoS1 |
| 2017 | Perez, T., Bawden, O., Kulk, J., Russell, R., McCool, C., English, A., & Dayoub, F. (2017). Overview of mechatronic design for a weed-management robotic system. In D. Zhang, & B. Wei (Eds.), Robotics and Mechatronics for Agriculture (1st ed., pp. 23-49). Boca Raton, USA: CRC Press. DOI |
| 2015 | Dayoub, F., Cielniak, G., & Duckett, T. (2015). Eight weeks of episodic visual navigation inside a non-stationary environment using adaptive spherical views. In L. Mejias, P. Corke, & J. Roberts (Eds.), Springer Tracts in Advanced Robotics (Vol. 105, pp. 379-392). SPRINGER-VERLAG BERLIN. DOI Scopus2 WoS2 |
| 2011 | Dayoub, F., Cielniak, G., & Duckett, T. (2011). Long-term experiment using an adaptive appearance-based map for visual navigation by mobile robots. In Lecture Notes in Computer Science (Vol. 6856 LNAI, pp. 400-401). Springer Berlin Heidelberg. DOI Scopus1 |
| Year | Citation |
|---|---|
| 2026 | Lin, C., Chin, T. -J., Garg, S., & Dayoub, F. (2026). SceneEdited: A City-Scale Benchmark for 3D HD Map Updating via Image-Guided Change Detection. In SceneEdited: A City-Scale Benchmark for 3D HD Map Updating via Image-Guided Change Detection. Tucson, Arizona. |
| 2025 | Garg, S., Craggs, D., Bhat, V., Mares, L., Podgorski, S., Krishna, M., . . . Reid, I. (2025). ObjectReact: Learning Object-Relative Control for Visual Navigation. In J. Lim, S. Song, & H. W. Park (Eds.), CONFERENCE ON ROBOT LEARNING Vol. 305 (pp. 1397-1419). SOUTH KOREA: JMLR-JOURNAL MACHINE LEARNING RESEARCH. |
| 2025 | Ma-Wyatt, A., Dayoub, F., de Zwart, M., & Culton, J. (2025). Robots supervising humans and humans supervising robots - a call for new concepts in human-robot teaming in space. In Proceedings of the International Astronautical Congress Iac (pp. 312-316). International Astronautical Federation (IAF). DOI |
| 2025 | Holden, L., Dayoub, F., Candela, A., Harvey, D., & Chin, T. J. (2025). Vision Foundation Models for Domain Generalisable Cross-View Localisation in Planetary Ground-Aerial Robotic Teams. In 2025 International Conference on Space Robotics Isparo 2025 (pp. 154-160). IEEE. DOI |
| 2025 | Abraham, S. S., Garg, S., & Dayoub, F. (2025). To Ask or Not to Ask? Detecting Absence of Information in Vision and Language Navigation. In Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (pp. 7480-7489). Tucson, AZ, USA Funding Agency: Authors Savitha Sam Abraham Australian Institute for Machine Learning, The University of Adelaide, Australia Sourav Garg Australian Institute for Machine Learning, The University of Adelaide, Australia Feras Dayoub Australian Institute for Machine Learning, The University of Adelaide, Australia Figures References Keywords Metrics Contact IEEE to Subscribe: IEEE. DOI |
| 2025 | Chapman, N. H., Lehnert, C., Browne, W., & Dayoub, F. (2025). Enhancing Embodied Object Detection with Spatial Feature Memory. In Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (pp. 6921-6931). Tucson, AZ, USA: IEEE. DOI Scopus2 WoS1 |
| 2025 | Shi, X., Qiao, Y., Liu, L., & Dayoub, F. (2025). Embodied Domain Adaptation for Object Detection. In C. Laugier, N. Atanasov, S. Birchfield, G. Cielniak, L. DeMattos, L. Fiorini, . . . H. Zhao (Eds.), IEEE International Conference on Intelligent Robots and Systems (pp. 15119-15126). PEOPLES R CHINA, Hangzhou: IEEE. DOI |
| 2025 | Shi, X., Li, Z., Lyu, W., Xia, J., Dayoub, F., Qiao, Y., & Wu, Q. (2025). SmartWay: Enhanced Waypoint Prediction and Backtracking for Zero-Shot Vision-and-Language Navigation. In C. Laugier, N. Atanasov, S. Birchfield, G. Cielniak, L. DeMattos, L. Fiorini, . . . H. Zhao (Eds.), IEEE International Conference on Intelligent Robots and Systems (pp. 16923-16930). PEOPLES R CHINA, Hangzhou: IEEE. DOI Scopus1 |
| 2025 | Podgorski, S., Garg, S., Hosseinzadeh, M., Mares, L., Dayoub, F., & Reid, I. (2025). TANGO: Traversability-Aware Navigation with Local Metric Control for Topological Goals. In 2025 IEEE International Conference on Robotics and Automation (ICRA) (pp. 2399-2406). Atlanta, GA, USA: IEEE. DOI WoS1 |
| 2025 | Deng, J., He, T., Jiang, L., Wang, T., Dayoub, F., & Reid, I. (2025). 3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 3772-3782). TN, Nashville: IEEE COMPUTER SOC. DOI Scopus5 WoS2 |
| 2025 | Lin, C. -J., Garg, S., Chin, T. -J., & Dayoub, F. (2025). Robust Scene Change Detection Using Visual Foundation Models and Cross-Attention Mechanisms. In 2025 IEEE International Conference on Robotics and Automation (ICRA) (pp. 8337-8343). Atlanta, GA, USA: IEEE. DOI Scopus1 |
| 2025 | Zhang, W., Li, Y., Qiao, Y., Huang, S., Liu, J., Dayoub, F., . . . Liu, L. (2025). Effective Tuning Strategies for Generalist Robot Manipulation Policies. In 2025 IEEE International Conference on Robotics and Automation (ICRA) (pp. 7255-7262). Atlanta, GA, USA: IEEE. DOI Scopus1 |
| 2025 | Chapman, N. H., Dayoub, F., Browne, W., & Lehnert, C. (2025). QueryAdapter: Rapid Adaptation of Vision-Language Models in Response to Natural Language Queries. In C. Laugier, N. Atanasov, S. Birchfield, G. Cielniak, L. DeMattos, L. Fiorini, . . . H. Zhao (Eds.), IEEE International Conference on Intelligent Robots and Systems (pp. 9606-9613). PEOPLES R CHINA, Hangzhou: IEEE. DOI |
| 2024 | McLeod, S., Chng, C. K., Ono, T., Shimizu, Y., Hemmi, R., Holden, L., . . . Chin, T. J. (2024). Robust Perspective-n-Crater for Crater-based Camera Pose Estimation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 6760-6769). Seattle: IEEE. DOI Scopus6 WoS5 |
| 2024 | Yuan, D., Maire, F., & Dayoub, F. (2024). Temporal Attention for Cross-View Sequential Image Localization. In IEEE International Conference on Intelligent Robots and Systems (pp. 7429-7436). Abu Dhabi, United Arab Emirates: IEEE. DOI |
| 2024 | Abou-Chakra, J., Rana, K., Dayoub, F., & Sünderhauf, N. (2024). Physically Embodied Gaussian Splatting: A Visually Learnt and Physically Grounded 3D Representation for Robotics. In Proceedings of Machine Learning Research Vol. 270 (pp. 513-530). Munich, Germany: ML Research Press. Scopus5 |
| 2024 | Wilson, S., Fischer, T., Dayoub, F., Miller, D., & Sünderhauf, N. (2024). SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023) (pp. 23508-23519). online: IEEE. DOI Scopus39 WoS31 |
| 2024 | Wu, R., Wang, H., Dayoub, F., & Chen, H. T. (2024). Segment beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 6100-6108). Online: Association for the Advancement of Artificial Intelligence (AAAI). DOI Scopus11 WoS6 |
| 2024 | Yuan, D., Maire, F., & Dayoub, F. (2024). Cross-Attention between Satellite and Ground Views for Enhanced Fine-Grained Robot Geo-Localization. In Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 (pp. 1238-1245). Online: IEEE. DOI Scopus8 WoS2 |
| 2024 | Abou-Chakra, J., Dayoub, F., & Sunderhauf, N. (2024). ParticleNeRF: A Particle-Based Encoding for Online Neural Radiance Fields. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2024) (pp. 5963-5972). Online: IEEE. DOI Scopus16 WoS1 |
| 2024 | Garg, S., Rana, K., Hosseinzadeh, M., Mares, L., Sünderhauf, N., Dayoub, F., & Reid, I. (2024). RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 35 (pp. 4090-4097). Yokohama, Japan: IEEE. DOI Scopus15 WoS7 |
| 2023 | Wilson, S., Fischer, T., Sunderhauf, N., & Dayoub, F. (2023). Hyperdimensional Feature Fusion for Out-of-Distribution Detection. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2023) (pp. 2643-2653). Online: IEEE. DOI Scopus16 WoS17 |
| 2022 | Corke, P., Dayoub, F., Hall, D., Skinner, J., & Sünderhauf, N. (2022). What Can Robotics Research Learn from Computer Vision Research?. In Proceedings of the 19th International Symposium of Robotic Research (ISRR 2019), as published in Springer Proceedings in Advanced Robotics Vol. 20 (pp. 987-1003). Cham, Switzerland: Springer. DOI |
| 2021 | Moskvyak, O., Maire, F., Dayoub, F., Armstrong, A. O., & Baktashmotlagh, M. (2021). Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. In DICTA 2021 - 2021 International Conference on Digital Image Computing: Techniques and Applications (pp. 1-8). online: IEEE. DOI Scopus28 WoS18 |
| 2021 | Bista, S. R., Hall, D., Talbot, B., Zhang, H., Dayoub, F., & Sünderhauf, N. (2021). Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 5328-5335). online: IEEE. DOI Scopus10 WoS8 |
| 2021 | Miller, D., Sunderhauf, N., Milford, M., & Dayoub, F. (2021). Class anchor clustering: A loss for distance-based open set recognition. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2021) (pp. 3569-3577). online: IEEE. DOI Scopus161 WoS122 |
| 2021 | Moskvyak, O., Maire, F., Dayoub, F., & Baktashmotlagh, M. (2021). Keypoint-aligned embeddings for image retrieval and re-identification. In Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 (pp. 676-685). online: IEEE. DOI Scopus28 WoS25 |
| 2021 | Zhang, H., Wang, Y., Dayoub, F., & Sünderhauf, N. (2021). VarifocalNet: An IoU-aware Dense Object Detector. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 8510-8519). online: IEEE. DOI Scopus1128 WoS949 |
| 2021 | Rahman, Q. M., Sunderhauf, N., & Dayoub, F. (2021). Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection during Deployment. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshops (WACVW 2021) (pp. 152-160). online: IEEE. DOI Scopus18 WoS17 |
| 2021 | Rahman, Q. M., Sünderhauf, N., & Dayoub, F. (2021). Online Monitoring of Object Detection Performance During Deployment. In Proceedings of the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021) (pp. 4839-4845). online: IEEE. DOI Scopus14 WoS12 |
| 2021 | Moskvyak, O., Maire, F., Dayoub, F., & Baktashmotlagh, M. (2021). SEMI-SUPERVISED KEYPOINT LOCALIZATION. In ICLR 2021 - 9th International Conference on Learning Representations (pp. 1-11). Virtual only: Open Review. Scopus18 |
| 2020 | Moskvyak, O., Maire, F., Dayoub, F., & Baktashmotlagh, M. (2020). Learning Landmark Guided Embeddings for Animal Re-identification. In 2020 IEEE Winter Applications of Computer Vision Workshops (WACVW) (pp. 12-19). online: IEEE. DOI Scopus13 WoS12 |
| 2020 | Hall, D., Dayoub, F., Skinner, J., Zhang, H., Miller, D., Corke, P., . . . Sunderhauf, N. (2020). Probabilistic object detection: Definition and evaluation. In Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 (pp. 1020-1029). online: IEEE. DOI Scopus95 WoS73 |
| 2019 | Halodova, L., Dvorrakova, E., Majer, F., Vintr, T., Mozos, O. M., Dayoub, F., & Krajnik, T. (2019). Predictive and adaptive maps for long-term visual navigation in changing environments. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 7033-7039). Macau, China: IEEE. DOI Scopus22 WoS19 |
| 2019 | Miller, D., Dayoub, F., Milford, M., & Sunderhauf, N. (2019). Evaluating merging strategies for sampling-based uncertainty techniques in object detection. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2019) (pp. 2348-2354). online: IEEE. DOI Scopus100 WoS81 |
| 2019 | Rahman, Q. M., Sunderhauf, N., & Dayoub, F. (2019). Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3748-3753). online: IEEE. DOI Scopus24 WoS24 |
| 2019 | Miller, D., Sünderhauf, N., Zhang, H., Hall, D., & Dayoub, F. (2019). Benchmarking sampling-based probabilistic object detectors. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2019-June (pp. 42-45). Scopus12 |
| 2018 | Abbas, A., Maire, F., Shirazi, S., Dayoub, F., & Eich, M. (2018). A dynamic planner for object assembly tasks based on learning the spatial relationships of its parts from a single demonstration. In T. Mitrovic, B. Xue, & X. Li (Eds.), Proceedings of AI 2018: Advanced in Artificial Intelligence 31st Australasian Joint Conference Vol. 11320 LNAI (pp. 759-765). Wellington, New Zealand: Springer International Publishing. DOI Scopus2 |
| 2018 | McFadyen, A., Dayoub, F., Martin, S., Ford, J., & Corke, P. (2018). Assisted Control for Semi-Autonomous Power Infrastructure Inspection Using Aerial Vehicles. In IEEE International Conference on Intelligent Robots and Systems (pp. 5719-5726). online: IEEE. DOI Scopus3 WoS3 |
| 2018 | Miller, D., Nicholson, L., Dayoub, F., & Sunderhauf, N. (2018). Dropout Sampling for Robust Object Detection in Open-Set Conditions. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2018) (pp. 3243-3249). Brisbane, Australia: IEEE. DOI Scopus230 WoS191 |
| 2018 | Abbas, A., Maire, F., Dayoub, F., & Shirazi, S. (2018). Combining learning from demonstration and search algorithm for dynamic goal-directed assembly task planning. In ACRA 2018 Proceedings Vol. 2018-December. Online: Australian Robotics and Automation Association. |
| 2017 | Dayoub, F., Sunderhauf, N., & Corke, P. I. (2017). Episode-Based Active Learning with Bayesian Neural Networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2017) Vol. 2017-July (pp. 498-500). Honolulu, Hawaii, USA: IEEE. DOI Scopus9 WoS5 |
| 2017 | Hall, D., Dayoub, F., Kulk, J., & McCool, C. (2017). Towards unsupervised weed scouting for agricultural robotics. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 5223-5230). online: IEEE. DOI Scopus40 |
| 2017 | Hall, D., Dayoub, F., Perez, T., & McCool, C. (2017). A transplantable system for weed classification by agricultural robotics. In 2017 IEEE International Conference on Intelligent Robots and Systems Vol. 2017-September (pp. 5174-5179). Vancouver, BC, Canada: IEEE. DOI Scopus6 WoS4 |
| 2016 | Sunderhauf, N., Dayoub, F., McMahon, S., Talbot, B., Schulz, R., Corke, P., . . . Milford, M. (2016). Place categorization and semantic mapping on a mobile robot. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 2016-June (pp. 5729-5736). online: IEEE. DOI Scopus132 WoS101 |
| 2016 | McCool, C., Sa, I., Dayoub, F., Lehnert, C., Perez, T., & Upcroft, B. (2016). Visual detection of occluded crop: For automated harvesting. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 2016-June (pp. 2506-2512). Stockholm, Sweden: IEEE. DOI Scopus69 WoS55 |
| 2016 | Talbot, B., Lam, O., Schulz, R., Dayoub, F., Upcroft, B., & Wyeth, G. (2016). Find my office: Navigating real space from semantic descriptions. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 2016-June (pp. 5782-5787). online: IEEE. DOI Scopus19 WoS12 |
| 2015 | Schulz, R., Talbot, B., Lam, O., Dayoub, F., Corke, P., Upcroft, B., & Wyeth, G. (2015). Robot navigation using human cues: A robot navigation system for symbolic goal-directed exploration. In Proceedings IEEE International Conference on Robotics and Automation Vol. 2015-June (pp. 1100-1105). Seattle, WA: IEEE COMPUTER SOC. DOI Scopus28 WoS16 |
| 2015 | Dayoub, F., Dunbabin, M., & Corke, P. (2015). Robotic detection and tracking of Crown-of-Thorns starfish. In IEEE International Conference on Intelligent Robots and Systems Vol. 2015-December (pp. 1921-1928). Hamburg, GERMANY: IEEE. DOI Scopus37 WoS26 |
| 2015 | Sünderhauf, N., Shirazi, S., Jacobson, A., Dayoub, F., Pepperell, E., Upcroft, B., & Milford, M. (2015). Place recognition with convnet landmarks: Viewpoint-robust, condition-robust, training-free. In Proceedings of the Robotics: Science and Systems XI Conference (RSS 2015) Vol. 11 (pp. 1-10). online: Robotics: Science and Systems Foundation. DOI Scopus336 WoS201 |
| 2015 | Hall, D., McCool, C., Dayoub, F., Sünderhauf, N., & Upcroft, B. (2015). Evaluation of features for leaf classification in challenging conditions. In Proceedings 2015 IEEE Winter Conference on Applications of Computer Vision Wacv 2015 (pp. 797-804). HI, Waikoloa: IEEE. DOI Scopus116 WoS80 |
| 2015 | Sünderhauf, N., Shirazi, S., Dayoub, F., Upcroft, B., & Milford, M. (2015). On the performance of ConvNet features for place recognition. In IEEE International Conference on Intelligent Robots and Systems Vol. 2015-December (pp. 4297-4304). Hamburg, GERMANY: IEEE. DOI Scopus488 WoS400 |
| 2015 | Lam, O., Dayoub, F., Schulz, R., & Corke, P. (2015). Automated topometric graph generation from floor plan analysis. In Australasian Conference on Robotics and Automation Acra. Scopus9 |
| 2014 | Lam, O., Dayoub, F., Schulz, R., & Corke, P. (2014). Text recognition approaches for indoor robotics: A comparison. In Australasian Conference on Robotics and Automation Acra Vol. 02-04-December-2014. Scopus4 |
| 2014 | Morris, T., Dayoub, F., Corke, P., & Upcroft, B. (2014). Simultaneous localization and planning on multiple map hypotheses. In IEEE International Conference on Intelligent Robots and Systems (pp. 4531-4536). Chicago, IL: IEEE. DOI Scopus5 WoS5 |
| 2014 | Morris, T., Dayoub, F., Corke, P., Wyeth, G., & Upcroft, B. (2014). Multiple map hypotheses for planning and navigating in non-stationary environments. In Proceedings IEEE International Conference on Robotics and Automation (pp. 2765-2770). Hong Kong, PEOPLES R CHINA: IEEE. DOI Scopus20 WoS15 |
| 2013 | Dayoub, F., Morris, T., Upcroft, B., & Corke, P. (2013). Vision-only autonomous navigation using topometric maps. In N. Amato (Ed.), IEEE International Conference on Intelligent Robots and Systems (pp. 1923-1929). JAPAN, Tokyo: IEEE. DOI Scopus36 WoS24 |
| 2013 | Dayoub, F., Morris, T., Upcroft, B., & Corke, P. (2013). One Robot, eight hours, and twenty four thousand people. In Australasian Conference on Robotics and Automation Acra. Scopus1 |
| 2010 | Dayoub, F., Duckett, T., & Cielniak, G. (2010). Short- and long-term adaptation of visual place memories for mobile robots. In Proceedings of the International Symposium on Remembering Who We are Human Memory for Artificial Agents A Symposium at the Aisb 2010 Convention (pp. 21-26). Scopus2 |
| 2008 | Dayoub, F., & Duckett, T. (2008). An adaptive appearance-based map for long-term topological localization of mobile robots. In R. Chatila, A. Kelly, & J. P. Merlet (Eds.), 2008 IEEE Rsj International Conference on Intelligent Robots and Systems Iros (pp. 3364-3369). Nice, FRANCE: IEEE. DOI Scopus79 WoS56 |
| Year | Citation |
|---|---|
| 2024 | Mallick, P., Dayoub, F., & Sherrah, J. (2024). Wasserstein Distance-based Expansion of Low-Density Latent Regions for Unknown Class Detection. |
| 2024 | Yuan, D., Maire, F., & Dayoub, F. (2024). Temporal Attention for Cross-View Sequential Image Localization. |
| 2024 | Lin, C. -J., Garg, S., Chin, T. -J., & Dayoub, F. (2024). Robust Scene Change Detection Using Visual Foundation Models and Cross-Attention Mechanisms. |
| 2024 | Bockman, J., Howe, M., Orenstein, A., & Dayoub, F. (2024). AARK: An Open Toolkit for Autonomous Racing Research. |
| 2024 | Garg, S., Rana, K., Hosseinzadeh, M., Mares, L., Sünderhauf, N., Dayoub, F., & Reid, I. (2024). RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation. |
| 2024 | Abraham, S. S., Garg, S., & Dayoub, F. (2024). To Ask or Not to Ask? Detecting Absence of Information in Vision and Language Navigation. |
| 2024 | Abou-Chakra, J., Rana, K., Dayoub, F., & Sünderhauf, N. (2024). Physically Embodied Gaussian Splatting: A Realtime Correctable World Model for Robotics. |
| 2023 | Holden, L., Dayoub, F., Harvey, D., & Chin, T. -J. (2023). Federated Neural Radiance Fields. |
| 2023 | Wu, R., Wang, H., Dayoub, F., & Chen, H. -T. (2023). Segment Beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation. |
| 2022 | Wilson, S., Fischer, T., Dayoub, F., Miller, D., & Sünderhauf, N. (2022). SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection. |
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2026 | Principal Supervisor | Learning Continuous, Corrective Behaviours for Embodied Control | Doctor of Philosophy | Doctorate | Full Time | Mr Lishan Yang |
| 2026 | Principal Supervisor | Run-Time Monitoring of Machine Learning for Robotic and Autonomous Perception | Doctor of Philosophy | Doctorate | Full Time | Mr One il Chiang |
| 2025 | Co-Supervisor | Exploring Human-Robot Interaction as a Collaborative Model for One-to-Many Teaming in Aerospace Environments | Doctor of Philosophy | Doctorate | Full Time | Mrs Donna Lee Duffy |
| 2025 | Co-Supervisor | Low-Cost Implementation of Visual Pseudo-Tactile and Multitasking Imitation Learning | Master of Philosophy | Master | Full Time | Mr Yukun Chen |
| 2025 | Co-Supervisor | Exploring Human-Robot Interaction as a Collaborative Model for One-to-Many Teaming in Aerospace Environments | Doctor of Philosophy | Doctorate | Full Time | Mrs Donna Lee Duffy |
| 2025 | Co-Supervisor | Low-Cost Implementation of Visual Pseudo-Tactile and Multitasking Imitation Learning | Master of Philosophy | Master | Full Time | Mr Yukun Chen |
| 2024 | Principal Supervisor | Foundation models for goal-oriented reinforcement learning and intrinsic exploration | Master of Philosophy | Master | Full Time | Mr Dustin Wyly Craggs |
| 2024 | Principal Supervisor | Robust Machine Learning Techniques for RF Signal Classification on Sparse and Noisy Digitally Sampled Radar Data | Master of Philosophy | Master | Full Time | Mr Sebastian Luke McCormack Cocks |
| 2024 | Co-Supervisor | Hand-held Object Identification, Segmentation, and Tracking in the Wild | Doctor of Philosophy | Doctorate | Full Time | Mr Huy Anh Nguyen |
| 2024 | Principal Supervisor | Data-driven physically plausible dexterous manipulation | Doctor of Philosophy | Doctorate | Full Time | Mr King Hang Wong |
| 2024 | Principal Supervisor | Foundation models for goal-oriented reinforcement learning and intrinsic exploration | Master of Philosophy | Master | Full Time | Mr Dustin Wyly Craggs |
| 2024 | Co-Supervisor | Hand-held Object Identification, Segmentation, and Tracking in the Wild | Doctor of Philosophy | Doctorate | Full Time | Mr Huy Anh Nguyen |
| 2024 | Principal Supervisor | Data-driven physically plausible dexterous manipulation | Doctor of Philosophy | Doctorate | Full Time | Mr King Hang Wong |
| 2024 | Principal Supervisor | Robust Machine Learning Techniques for RF Signal Classification on Sparse and Noisy Digitally Sampled Radar Data | Master of Philosophy | Master | Full Time | Mr Sebastian Luke McCormack Cocks |
| 2023 | Principal Supervisor | 3D Scene Understanding and Change Tracking | Doctor of Philosophy | Doctorate | Full Time | Mr Chun-Jung Lin |
| 2023 | Co-Supervisor | 3D indoor Scene Reconstruction | Doctor of Philosophy | Doctorate | Full Time | Mr Wenbo Zhang |
| 2023 | Co-Supervisor | 3D indoor Scene Reconstruction | Doctor of Philosophy | Doctorate | Full Time | Mr Wenbo Zhang |
| 2023 | Principal Supervisor | 3D Scene Understanding and Change Tracking | Doctor of Philosophy | Doctorate | Full Time | Mr Chad Lin |
| 2022 | Co-Supervisor | Enhancing Mars rovers using AI-enabled robotic vision | Doctor of Philosophy | Doctorate | Full Time | Mr Lachlan William Holden |
| 2022 | Co-Supervisor | Enhancing Mars rovers using AI-enabled robotic vision | Doctor of Philosophy | Doctorate | Full Time | Mr Lachlan William Holden |
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2023 - 2025 | Principal Supervisor | Foundation Models for Embodied Navigation | Doctor of Philosophy | Master | Full Time | Mr Xiangyu Shi |
| 2022 - 2024 | Co-Supervisor | Towards Pedestrian Safety Augmented Reality System | Master of Philosophy | Master | Full Time | Mr Renjie Wu |
