activity
20182025
most citedSurf-NeRF: Surface Regularised Neural Radiance Fields

1 citations · 2 across the 14 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

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…

cs.CV20241 cited

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…

cs.CV2024

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…

cs.RO2024

Mixing Data-driven and Geometric Models for Satellite Docking Port State Estimation using an RGB or Event Camera

Cedric Le Gentil, Jack Naylor, Nuwan Munasinghe +5

In-orbit automated servicing is a promising path towards lowering the cost of satellite operations and reducing the amount of orbital debris. For this purpose, we present a pipelin…

cs.CV2024

Adapting CNNs for Fisheye Cameras without Retraining

Ryan Griffiths, Donald G. Dansereau

The majority of image processing approaches assume images are in or can be rectified to a perspective projection. However, in many applications it is beneficial to use non conventi…