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2015 Conference Papers [53]

Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control

*Zhang, F., Leitner, J., Milford, M., Upcroft, B., & Corke, P. (2015). Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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ORB Feature Extraction and Matching in Hardware

*Weberruss, J., Kleeman, L., & Drummond, T. (2015). ORB Feature Extraction and Matching in Hardware. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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Self-Calibration in Visual Sensor Networks Equipped with RGB-D Cameras

*Wang, X., Sekercioglu, Y. A., & Drummond, T. (2015). Self-calibration in visual sensor networks equipped with RGB-D cameras. Paper presented at the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015, South Brisbane, QLD.

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Efficient SDP Inference for Fully-connected CRFs Based on Low-rank Decomposition

*Wang, P., Shen, C., & van den Hengel, A. (2015). Efficient SDP inference for fully-connected CRFs based on low-rank decomposition. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Piscataway, NJ, USA.

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Continuous Factor Graphs for Holistic Scene Understanding

*Sünderhauf, N., Upcroft, B., & Milford, M. (2015). Continuous Factor Graphs For Holistic Scene Understanding. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

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On the Performance of ConvNet Features for Place Recognition

*Sünderhauf, N., Dayoub, F., Shirazi, S., Upcroft, B., & Milford, M. (2015). On the Performance of ConvNet Features for Place Recognition. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

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SLAM – Quo Vadis? In Support of Object Oriented and Semantic SLAM

*Sünderhauf, N., Dayoub, F., McMahon, S., Eich, M., Upcroft, B., & Milford, M. (2015). SLAM–Quo Vadis? In Support of Object Oriented and Semantic SLAM. Paper presented at the Robotics: Science and Systems (RSS) 2015, Rome, Italy.

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A Fast Method For Computing Principal Curvatures From Range Images

*Spek, A., & Drummond, T. (2015). A Fast Method For Computing Principal Curvatures From Range Images. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning

*Sokeh, H. S., Gould, S., & Renz, J. (2015). Determining interacting objects in human-centric activities via qualitative spatio-temporal reasoning. Paper presented at the Asian Conference on Computer Vision (ACCV) 1-5 Nov. 2014, Cham, Switzerland.

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Multimodal Deep Autoencoders for Control of a Mobile Robot

*Sergeant, J., Sünderhauf, N., Milford, M., & Upcroft, B. (2015). Multimodal Deep Autoencoders for Control of a Mobile Robot. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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Trajectory Alignment and Evaluation in SLAM: Horn’s Method vs Alignment on the Manifold

*Salas, M., Latif, Y., Reid, I. D., & Montiel, J. (2015). Trajectory Alignment and Evaluation in SLAM: Horn’s Method vs Alignment on the Manifold. Paper presented at the Robotics: Science and Systems (RSS) 2015.

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Enhancing Human Action Recognition with Region Proposals

*Rezazadegan, F., Shirazi, S., Sunderhauf, N., Milford, M., & Upcroft, B. (2015). Enhancing human action recognition with region proposals. Paper presented at the Australasian Conference on Robotics and Automation (ACRA2015), Australian National University, Canberra.

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Evaluation of Object Detection Proposals Under Condition Variations

*Rezazadegan, F., Shirazi, S., Milford, M., & Upcroft, B. (2015). Evaluation of object detection proposals under condition variations. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Boston, Mass.

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The Effect of Different Parameterisations in Incremental Structure from Motion

*Polok, L., Lui, V., Ila, V., Drummond, T., & Mahony, R. (2015). The Effect of Different Parameterisations in Incremental Structure from Motion. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015, Canberra, Australia.

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Hierarchical Higher-order Regression Forest Fields: An Application to 3D Indoor Scene Labelling

*Pham, T. T., Reid, I., Latif, Y., & Gould, S. (2015). Hierarchical Higher-order Regression Forest Fields: An Application to 3D Indoor Scene Labelling. Paper presented at the International Conference on Computer Vision (ICCV) 2015.

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Automatic Image Scaling for Place Recognition in Changing Environments

*Pepperell, E., Corke, P. I., & Milford, M. J. (2015). Automatic image scaling for place recognition in changing environments. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015, Piscataway, NJ, USA.

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Effective Semantic Pixel labelling with Convolutional Networks and Conditional Random Fields

*Paisitkriangkrai, S., Sherrah, J., Janney, P., & Van-Den Hengel, A. (2015). Effective semantic pixel labelling with convolutional networks and conditional random fields. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Piscataway, NJ, USA.

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Monocular Image Space Tracking on a Computationally Limited MAV

*Ok, K., Gamage, D., Drummond, T., Dellaert, F., & Roy, N. (2015). Monocular image space tracking on a computationally limited MAV. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015.

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Sequence Searching with Deep-learnt Depth for Condition- and Viewpointinvariant Route-based Place Recognition

*Milford, M., Shen, C., Lowry, S., Suenderhauf, N., Shirazi, S., Lin, G., Upcroft, B. (2015). Sequence Searching with Deep-learnt Depth for Condition-and Viewpoint-invariant Route-based Place Recognition. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

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How Good Are Edge Boxes, Really?

*McMahon, S., Sünderhauf, N., Upcroft, B., & Milford, M. (2015). How Good Are EdgeBoxes, Really. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

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TripNet: Detecting Trip Hazards on Construction Sites

*McMahon, S., Sünderhauf, N., Milford, M., & Upcroft, B. (2015). TripNet:Detecting Trip Hazards on Construction Sites. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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A Shallow Water AUV for Benthic and Water Column Observations

*Marouchos, A., Muir, B., Babcock, R., & Dunbabin, M. (2015). A shallow water AUV for benthic and water column observations. Paper presented at the MTS/IEEE OCEANS, 2015, Piscataway, NJ, USA.

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A Linear Least-Squares Solution to Elastic Shape-from-Template

*Malti, A., Bartoli, A., & Hartley, R. (2015). A Linear Least-Squares Solution to Elastic Shape-from-Template. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

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Automating Marine Mammal Detection in Aerial Images Captured During Wildlife Surveys: a Deep Learning Approach

*Maire, F., Alvarez, L. M., & Hodgson, A. (2015). Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach. Paper presented at the AI 2015: Advances in Artificial Intelligence.

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Fast Inverse Compositional Image Alignment with Missing Data and Re-weighting

*Lui, V., Gamage, D., & Drummond, T. (2015). Fast Inverse Compositional Image Alignment with Missing Data and Re-weighting. Paper presented at the British Machine Vision Conference (BMVC) 2015, Swansea, UK.

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Image Based Optimisation without Global Consistency for Constant Time Monocular Visual SLAM

*Lui, V., & Drummond, T. (2015). Image based optimisation without global consistency for constant time monocular visual SLAM. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015, Piscataway, NJ, USA.

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Deeply Learning the Messages in Message Passing Inference

*Lin, G., Shen, C., Reid, I., & Hengel, A. v. d. (2015). Deeply Learning the Messages in Message Passing Inference. Paper presented at the Neural Information Processing Systems (NIPS), 2015, Montreal, Canada.

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The use of Deep Learning Features in a Hierarchical Classifier Learned with the Minimization of a Non-Greedy Loss Function that Delays Gratification

*Liao, Z., & Carneiro, G. (2015). The use of deep learning features in a hierarchical classifier learned with the minimization of a non-greedy loss function that delays gratification. Paper presented at the IEEE International Conference on Image Processing (ICIP) 2015.

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The Need for Dynamic & Active Datasets

*Leitner, J., Dansereau, D. G., Shirazi, S., & Corke, P. (2015). The Need for Dynamic & Active Datasets. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Massachusetts, USA.

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Extending Visual Perception With Haptic Exploration for Improved Scene Understanding

*Leitner, J. (2015). Extending Visual Perception With Haptic Exploration for Improved Scene Understanding. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

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Guiding the Long-Short Term Memory model for Image Caption Generation

*Jia, X., Gavves, S., Fernando, B., & Tuytelaars, T. (2015). Guided long-short term memory for image caption generation. Paper presented at the International Conference on Computer Vision (ICCV) 2015.

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Online Place Recognition Calibration for Out-of-the-Box SLAM

*Jacobson, A., Zetao, C., & Milford, M. (2015). Online place recognition calibration for out-of-the-box SLAM. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, Piscataway, NJ, USA.

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Multi-Scale Place Recognition with Multi-Scale Sensing

*Jacobson, A., Chen, Z., Rallabandi, V. R., & Milford, M. (2015). Multi-Scale Place Recognition with Multi-Scale Sensing. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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Fast Covariance Recovery in Incremental Nonlinear Least Square Solvers

*Ila, V., Polok, L., Solony, M., Smrz, P., & Zemcik, P. (2015). Fast Covariance Recovery in Incremental Nonlinear Least Square Solvers. Paper presented at the IEEE International Conference on Robotics and Automation (ICRA), 2015, Seattle

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Robust Online Visual Tracking with a Single Convolutional Neural Network

*Hanxi, L., Yi, L., & Porikli, F. (2015). Robust online visual tracking with a single convolutional neural network. Paper presented at the Asian Conference on Computer Vision (ACCV) 1-5 Nov. 2014, Cham, Switzerland.

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Evaluation of Features for Leaf Classification in Challenging Conditions

*Hall, D., McCool, C., Dayoub, F., Sunderhauf, N., & Upcroft, B. (2015). Evaluation of Features for Leaf Classification in Challenging Conditions. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015, Los Alamitos, CA, USA

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Subset Feature Learning for Fine-Grained Category Classification

*Ge, Z., McCool, C., Sanderson, C., & Corke, P. (2015). Subset feature learning for fine-grained category classification. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, Piscataway, NJ, USA.

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Reduced Dimensionality Extended Kalman Filter for SLAM in a Relative Formulation

*Gamage, D., & Drummond, T. (2015). Reduced Dimensionality Extended Kalman Filter for SLAM. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

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Modeling Video Evolution For Action Recognition

*Fernando, B., Gavves, E., Oramas, J., Ghodrati, A., & Tuytelaars, T. (2015). Modeling video evolution for action recognition. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015

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Learning to Rank Based on Subsequences

*Fernando, B., Gavves, E., Muselet, D., & Tuytelaars, T. (2015). Learning to rank based on subsequences. Paper presented at the International Conference on Computer Vision (ICCV) 2015.

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Material Classification on Symmetric Positive Definite Manifolds

*Faraki, M., Harandi, M. T., & Porikli, F. (2015). Material Classification on Symmetric Positive Definite Manifolds. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015, Los Alamitos, CA, USA. http://dx.doi.org/10.1109/WACV.2015.105

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Towards Fuzzy Knowledge Based Scene Understanding from RGB-D Images

*Eich, M. (2015). Towards Fuzzy Knowledge Based Scene Understanding from RGB-D Images. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015

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Robotic Detection and Tracking of Crown-of-Thorns Starfish

*Dayoub, F., Dunbabin, M., & Corke, P. (2015). Robotic Detection and Tracking of Crown-of-Thorns Starfish. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, Hamburg, Germany

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Closed-Form Change Detection from Moving Light Field Cameras

*Dansereau, D. G., Williams, S. B., & Corke, P. I. (2015). Closed-Form Change Detection from Moving Light Field Cameras. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

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Coverage-Based Next Best View Selection

*Cunningham-Nelson, S., Moghadam, P., Roberts, J., & Elfes, A. (2015). Coverage-Based Next Best View Selection. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015.

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Distance Metric Learning for Feature-Agnostic Place Recognition

*Chen, Z., Lowry, S., Jacobson, A., Ge, Z., & Milford, M. (2015). Distance metric learning for feature-agnostic place recognition. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

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Distance Metric Learning for Feature-Agnostic Place Recognition

*Chen, Z., Lowry, S., Jacobson, A., Ge, Z., & Milford, M. (2015). Distance Metric Learning for Feature-Agnostic Place Recognition. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, Hamburg, Germany.

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Distributed Robotic Vision as a Service

*Chamberlain, W., Drummond, T., & Corke, P. (2015). Distributed Robotic Vision as a Service. Paper presented at the Australasian Conference on Robotics and Automation (ACRA) 2015, Canberra, Australia.

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Multi-class Semantic Video Segmentation with Exemplar-based Object Reasoning

*Buyu, L., Xuming, H., & Gould, S. (2015). Multi-class Semantic Video Segmentation with Exemplar-Based Object Reasoning. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015.

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From ImageNet to Mining: Adapting Visual Object Detection with Minimal Supervision

*Bewley, A., & Upcroft, B. (2015). From ImageNet to mining: Adapting visual object detection with minimal supervision. Paper presented at the Field and Service Robotics (FSR) 2015, University of Toronto, Canada

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Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex Priors

*Ajanthan, T., Hartley, R., Salzmann, M., & Li, H. (2015). Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex Priors. Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

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LQ-Bundle Adjustment

*Aftab, K., & Hartley, R. (2015). LQ-bundle adjustment. Paper presented at the IEEE International Conference on Image Processing (ICIP) 2015.

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Convergence of Iteratively Re-weighted Least Squares to Robust M-estimators

*Aftab, K., & Hartley, R. (2015). Convergence of Iteratively Re-weighted Least Squares to Robust M-Estimators. Paper presented at the IEEE Winter Conference on Applications of Computer Vision (WACV), 2015, Los Alamitos, CA, USA

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