7 citations · 7 across the 13 of their papers we have counts for
7 papers · 1 filter
Joint Multi-Condition Representation Modelling via Matrix Factorisation for Visual Place Recognition
Timur Ismagilov, Shakaiba Majeed, Michael Milford +3
We address multi-reference visual place recognition (VPR), where reference sets captured under varying conditions are used to improve localization performance. While deep learning…
Through the Lens of Doubt: Robust and Efficient Uncertainty Estimation for Visual Place Recognition
Emily Miller, Michael Milford, Muhammad Burhan Hafez +2
Visual Place Recognition (VPR) enables robots and autonomous vehicles to identify previously visited locations by matching current observations against a database of known places.…
Assessing the Geolocation Capabilities, Limitations and Societal Risks of Generative Vision-Language Models
Oliver Grainge, Sania Waheed, Jack Stilgoe +2
Geo-localization is the task of identifying the location of an image using visual cues alone. It has beneficial applications, such as improving disaster response, enhancing navigat…
VLM-Guided Visual Place Recognition for Planet-Scale Geo-Localization
Sania Waheed, Na Min An, Michael Milford +2
Geo-localization from a single image at planet scale (essentially an advanced or extreme version of the kidnapped robot problem) is a fundamental and challenging task in applicatio…
TAT-VPR: Ternary Adaptive Transformer for Dynamic and Efficient Visual Place Recognition
Oliver Grainge, Michael Milford, Indu Bodala +2
TAT-VPR is a ternary-quantized transformer that brings dynamic accuracy-efficiency trade-offs to visual SLAM loop-closure. By fusing ternary weights with a learned activation-spars…
TeTRA-VPR: A Ternary Transformer Approach for Compact Visual Place Recognition
Oliver Grainge, Michael Milford, Indu Bodala +2
Visual Place Recognition (VPR) localizes a query image by matching it against a database of geo-tagged reference images, making it essential for navigation and mapping in robotics.…
Image-based Geo-localization for Robotics: Are Black-box Vision-Language Models there yet?
Sania Waheed, Bruno Ferrarini, Michael Milford +2
The advances in Vision-Language models (VLMs) offer exciting opportunities for robotic applications involving image geo-localization - the problem of identifying the geo-coordinate…