20 citations · 50 across the 27 of their papers we have counts for
8 papers · 1 filter
Inductive Graph Few-shot Class Incremental Learning
Yayong Li, Peyman Moghadam, Can Peng +2
Node classification with Graph Neural Networks (GNN) under a fixed set of labels is well known in contrast to Graph Few-Shot Class Incremental Learning (GFSCIL), which involves lea…
Pair-VPR: Place-Aware Pre-training and Contrastive Pair Classification for Visual Place Recognition with Vision Transformers
Stephen Hausler, Peyman Moghadam
In this work we propose a novel joint training method for Visual Place Recognition (VPR), which simultaneously learns a global descriptor and a pair classifier for re-ranking. The…
A Deeper Look into Second-Order Feature Aggregation for LiDAR Place Recognition
Saimunur Rahman, Peyman Moghadam
Efficient LiDAR Place Recognition (LPR) compresses dense pointwise features into compact global descriptors. While first-order aggregators such as GeM and NetVLAD are widely used,…
Point-PNG: Conditional Pseudo-Negatives Generation for Point Cloud Pre-Training
Sutharsan Mahendren, Saimunur Rahman, Piotr Koniusz +4
We propose Point-PNG, a novel self-supervised learning framework that generates conditional pseudo-negatives in the latent space to learn point cloud representations that are both…
SOLVR: Submap Oriented LiDAR-Visual Re-Localisation
Joshua Knights, Sebastián Barbas Laina, Peyman Moghadam +1
This paper proposes SOLVR, a unified pipeline for learning based LiDAR-Visual re-localisation which performs place recognition and 6-DoF registration across sensor modalities. We p…
Object Registration in Neural Fields
David Hall, Stephen Hausler, Sutharsan Mahendren +1
Neural fields provide a continuous scene representation of 3D geometry and appearance in a way which has great promise for robotics applications. One functionality that unlocks uni…
Towards Long-term Robotics in the Wild
Stephen Hausler, Ethan Griffiths, Milad Ramezani +1
In this paper, we emphasise the critical importance of large-scale datasets for advancing field robotics capabilities, particularly in natural environments. While numerous datasets…
Reg-NF: Efficient Registration of Implicit Surfaces within Neural Fields
Stephen Hausler, David Hall, Sutharsan Mahendren +1
Neural fields, coordinate-based neural networks, have recently gained popularity for implicitly representing a scene. In contrast to classical methods that are based on explicit re…