7 papers · 1 filter
Learning Underwater Active Perception in Simulation
Alexandre Cardaillac, Donald G. Dansereau
When employing underwater vehicles for the autonomous inspection of assets, it is crucial to consider and assess the water conditions. These conditions significantly impact visibil…
Light Field Based 6DoF Tracking of Previously Unobserved Objects
Nikolai Goncharov, James L. Gray, Donald G. Dansereau
Object tracking is an important step in robotics and reautonomous driving pipelines, which has to generalize to previously unseen and complex objects. Existing high-performing meth…
JOCA: Task-Driven Joint Optimisation of Camera Hardware and Adaptive Camera Control Algorithms
Chengyang Yan, Mitch Bryson, Donald G. Dansereau
The quality of captured images strongly influences the performance of downstream perception tasks. Recent works on co-designing camera systems with perception tasks have shown impr…
Surf-NeRF: Surface Regularised Neural Radiance Fields
Jack Naylor, Viorela Ila, Donald G. Dansereau
Neural Radiance Fields (NeRFs) provide a high fidelity, continuous scene representation that can realistically represent complex behaviour of light. Despite works like Ref-NeRF imp…
Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting
Nikolai Goncharov, Donald G. Dansereau
Segmented light field images can serve as a powerful representation in many of computer vision tasks exploiting geometry and appearance of objects, such as object pose tracking. In…
LBurst: Learning-Based Robotic Burst Feature Extraction for 3D Reconstruction in Low Light
Ahalya Ravendran, Mitch Bryson, Donald G. Dansereau
Drones have revolutionized the fields of aerial imaging, mapping, and disaster recovery. However, the deployment of drones in low-light conditions is constrained by the image quali…