224 citations · 522 across the 48 of their papers we have counts for
45 papers · 1 filter
Direct initial orbit determination
Chee-Kheng Chng, Trent Jansen-Sturgeon, Timothy Payne +1
Initial orbit determination (IOD) is an important early step in the processing chain that makes sense of and reconciles the multiple optical observations of a resident space object…
Semantic Segmentation on 3D Point Clouds with High Density Variations
Ryan Faulkner, Luke Haub, Simon Ratcliffe +2
LiDAR scanning for surveying applications acquire measurements over wide areas and long distances, which produces large-scale 3D point clouds with significant local density variati…
Federated Neural Radiance Fields
Lachlan Holden, Feras Dayoub, David Harvey +1
The ability of neural radiance fields or NeRFs to conduct accurate 3D modelling has motivated application of the technique to scene representation. Previous approaches have mainly…
Assessing Domain Gap for Continual Domain Adaptation in Object Detection
Anh-Dzung Doan, Bach Long Nguyen, Surabhi Gupta +3
To ensure reliable object detection in autonomous systems, the detector must be able to adapt to changes in appearance caused by environmental factors such as time of day, weather,…
ROSIA: Rotation-Search-Based Star Identification Algorithm
Chee-Kheng Chng, Alvaro Parra Bustos, Benjamin McCarthy +1
This paper presents a rotation-search-based approach for addressing the star identification (Star-ID) problem. The proposed algorithm, ROSIA, is a heuristics-free algorithm that se…
Globally Optimal Event-Based Divergence Estimation for Ventral Landing
Sofia McLeod, Gabriele Meoni, Dario Izzo +5
Event sensing is a major component in bio-inspired flight guidance and control systems. We explore the usage of event cameras for predicting time-to-contact (TTC) with the surface…
Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing
Mohsi Jawaid, Ethan Elms, Yasir Latif +1
Deep models trained using synthetic data require domain adaptation to bridge the gap between the simulation and target environments. State-of-the-art domain adaptation methods ofte…
Update Compression for Deep Neural Networks on the Edge
Bo Chen, Ali Bakhshi, Gustavo Batista +2
An increasing number of artificial intelligence (AI) applications involve the execution of deep neural networks (DNNs) on edge devices. Many practical reasons motivate the need to…
Asynchronous Optimisation for Event-based Visual Odometry
Daqi Liu, Alvaro Parra, Yasir Latif +3
Event cameras open up new possibilities for robotic perception due to their low latency and high dynamic range. On the other hand, developing effective event-based vision algorithm…
A Hybrid Quantum-Classical Algorithm for Robust Fitting
Anh-Dzung Doan, Michele Sasdelli, David Suter +1
Fitting geometric models onto outlier contaminated data is provably intractable. Many computer vision systems rely on random sampling heuristics to solve robust fitting, which do n…
Adversarial Attacks against a Satellite-borne Multispectral Cloud Detector
Andrew Du, Yee Wei Law, Michele Sasdelli +4
Data collected by Earth-observing (EO) satellites are often afflicted by cloud cover. Detecting the presence of clouds -- which is increasingly done using deep learning -- is cruci…
Maximum Consensus by Weighted Influences of Monotone Boolean Functions
Erchuan Zhang, David Suter, Ruwan Tennakoon +4
Robust model fitting is a fundamental problem in computer vision: used to pre-process raw data in the presence of outliers. Maximisation of Consensus (MaxCon) is one of the most po…
Occlusion-Robust Object Pose Estimation with Holistic Representation
Bo Chen, Tat-Jun Chin, Marius Klimavicius
Practical object pose estimation demands robustness against occlusions to the target object. State-of-the-art (SOTA) object pose estimators take a two-stage approach, where the fir…
Physical Adversarial Attacks on an Aerial Imagery Object Detector
Andrew Du, Bo Chen, Tat-Jun Chin +4
Deep neural networks (DNNs) have become essential for processing the vast amounts of aerial imagery collected using earth-observing satellite platforms. However, DNNs are vulnerabl…
A Spacecraft Dataset for Detection, Segmentation and Parts Recognition
Dung Anh Hoang, Bo Chen, Tat-Jun Chin
Virtually all aspects of modern life depend on space technology. Thanks to the great advancement of computer vision in general and deep learning-based techniques in particular, ove…
Learning to Predict Repeatability of Interest Points
Anh-Dzung Doan, Daniyar Turmukhambetov, Yasir Latif +2
Many robotics applications require interest points that are highly repeatable under varying viewpoints and lighting conditions. However, this requirement is very challenging as the…
Spatiotemporal Registration for Event-based Visual Odometry
Daqi Liu, Alvaro Parra, Tat-Jun Chin
A useful application of event sensing is visual odometry, especially in settings that require high-temporal resolution. The state-of-the-art method of contrast maximisation recover…
Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging
Álvaro Parra, Shin-Fang Chng, Tat-Jun Chin +2
Under mild conditions on the noise level of the measurements, rotation averaging satisfies strong duality, which enables global solutions to be obtained via semidefinite programmin…
Consensus Maximisation Using Influences of Monotone Boolean Functions
Ruwan Tennakoon, David Suter, Erchuan Zhang +2
Consensus maximisation (MaxCon), which is widely used for robust fitting in computer vision, aims to find the largest subset of data that fits the model within some tolerance level…
HM4: Hidden Markov Model with Memory Management for Visual Place Recognition
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin +1
Visual place recognition needs to be robust against appearance variability due to natural and man-made causes. Training data collection should thus be an ongoing process to allow c…
Monocular Rotational Odometry with Incremental Rotation Averaging and Loop Closure
Chee-Kheng Chng, Alvaro Parra, Tat-Jun Chin +1
Estimating absolute camera orientations is essential for attitude estimation tasks. An established approach is to first carry out visual odometry (VO) or visual SLAM (V-SLAM), and…
Quantum Robust Fitting
Tat-Jun Chin, David Suter, Shin-Fang Chng +1
Many computer vision applications need to recover structure from imperfect measurements of the real world. The task is often solved by robustly fitting a geometric model onto noisy…
Auto-Rectify Network for Unsupervised Indoor Depth Estimation
Jia-Wang Bian, Huangying Zhan, Naiyan Wang +3
Single-View depth estimation using the CNNs trained from unlabelled videos has shown significant promise. However, excellent results have mostly been obtained in street-scene drivi…
Globally Optimal Contrast Maximisation for Event-based Motion Estimation
Daqi Liu, Álvaro Parra, Tat-Jun Chin
Contrast maximisation estimates the motion captured in an event stream by maximising the sharpness of the motion compensated event image. To carry out contrast maximisation, many p…