2 citations · 3 across the 16 of their papers we have counts for
19 papers
Artemis: Geometry-Grounded Multi-Agent Driving World Models with Shared 3D State and Progressive Memory Update
Sitian Shen, Jiuming Liu, Mengmeng Liu +7
Recent video world models have witnessed the paradigm shift from single-agent to multi-agent involvements, which can reveal more complicated dynamics and cross-agent interaction in…
InfraVLA: Extending Vision-Language-Action Navigation with Infrastructure Cameras
Lukas Vierling, Benjamin Ramtoula, Luke Robinson +2
Many indoor environments in which robots operate, such as warehouses, offices, and hospitals, already have cameras installed. They observe parts of the building that the robot cann…
Spotted: Location-informed Reidentification of Hyenas and Leopards in Camera Trap Surveys
Halil Sina Kelebek, Julia Hindel, Kobus Hoffman +9
Animal re-identification (ReID) in camera-trap surveys remains challenging due to low image quality, strong variation in illumination and viewpoint, and highly imbalanced numbers o…
PriorEye: Geospatial Visual Priors for End-to-End Autonomous Driving
Kyuhwan Yeon, Benjamin Ramtoula, Daniele De Martini
Most end-to-end autonomous driving methods rely solely on instantaneous sensor observations, limiting them to reactive behavior without the anticipatory foresight human drivers emp…
Beyond a Shadow of a Doubt: Close Proximity Geometry Reconstruction Using FMCW Radar Shadow Effects
Felix de Trogoff du Boisguezennec, Benjamin Ramtoula, Daniele De Martini
Reliable perception in adverse conditions remains challenging for autonomous systems, as cameras and LiDAR degrade in poor lighting or weather. Millimetre-wave FMCW radar is robust…
Introspection in Learned Semantic Scene Graph Localisation
Manshika Charvi Bissessur, Efimia Panagiotaki, Daniele De Martini
This work investigates how semantics influence localisation performance and robustness in a learned self-supervised, contrastive semantic localisation framework. After training a l…
Neural-MMGS: Multi-modal Neural Gaussian Splats for Large-Scale Scene Reconstruction
Sitian Shen, Georgi Pramatarov, Yifu Tao +1
This paper proposes Neural-MMGS, a novel neural 3DGS framework for multimodal large-scale scene reconstruction that fuses multiple sensing modalities in a per-gaussian compact, lea…
Ensemble of Pre-Trained Models for Long-Tailed Trajectory Prediction
Divya Thuremella, Yi Yang, Simon Wanna +2
This work explores the application of ensemble modeling to the multidimensional regression problem of trajectory prediction for vehicles in urban environments. As newer and bigger…
MinkOcc: Towards real-time label-efficient semantic occupancy prediction
Samuel Sze, Daniele De Martini, Lars Kunze
Developing 3D semantic occupancy prediction models often relies on dense 3D annotations for supervised learning, a process that is both labor and resource-intensive, underscoring t…
GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation
Efimia Panagiotaki, Georgi Pramatarov, Lars Kunze +1
Testing and validating Autonomous Vehicle (AV) performance in safety-critical and diverse scenarios is crucial before real-world deployment. However, manually creating such scenari…
NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
Efimia Panagiotaki, Daniele De Martini, Lars Kunze +2
This study explores the intersection of neural networks and classical robotics algorithms through the Neural Algorithmic Reasoning (NAR) blueprint, enabling the training of neural…
Watching Grass Grow: Long-term Visual Navigation and Mission Planning for Autonomous Biodiversity Monitoring
Matthew Gadd, Daniele De Martini, Luke Pitt +10
We describe a challenging robotics deployment in a complex ecosystem to monitor a rich plant community. The study site is dominated by dynamic grassland vegetation and is thus visu…
VDNA-PR: Using General Dataset Representations for Robust Sequential Visual Place Recognition
Benjamin Ramtoula, Daniele De Martini, Matthew Gadd +1
This paper adapts a general dataset representation technique to produce robust Visual Place Recognition (VPR) descriptors, crucial to enable real-world mobile robot localisation. T…
That's My Point: Compact Object-centric LiDAR Pose Estimation for Large-scale Outdoor Localisation
Georgi Pramatarov, Matthew Gadd, Paul Newman +1
This paper is about 3D pose estimation on LiDAR scans with extremely minimal storage requirements to enable scalable mapping and localisation. We achieve this by clustering all poi…
OORD: The Oxford Offroad Radar Dataset
Matthew Gadd, Daniele De Martini, Oliver Bartlett +11
There is a growing academic interest as well as commercial exploitation of millimetre-wave scanning radar for autonomous vehicle localisation and scene understanding. Although seve…
Mitigating Distributional Shift in Semantic Segmentation via Uncertainty Estimation from Unlabelled Data
David S. W. Williams, Daniele De Martini, Matthew Gadd +1
Knowing when a trained segmentation model is encountering data that is different to its training data is important. Understanding and mitigating the effects of this play an importa…
Masked Gamma-SSL: Learning Uncertainty Estimation via Masked Image Modeling
David S. W. Williams, Matthew Gadd, Paul Newman +1
This work proposes a semantic segmentation network that produces high-quality uncertainty estimates in a single forward pass. We exploit general representations from foundation mod…
Robot-Relay : Building-Wide, Calibration-Less Visual Servoing with Learned Sensor Handover Network
Luke Robinson, Matthew Gadd, Paul Newman +1
We present a system which grows and manages a network of remote viewpoints during the natural installation cycle for a newly installed camera network or a newly deployed robot flee…
What you see is what you get: Experience ranking with deep neural dataset-to-dataset similarity for topological localisation
Matthew Gadd, Benjamin Ramtoula, Daniele De Martini +1
Recalling the most relevant visual memories for localisation or understanding a priori the likely outcome of localisation effort against a particular visual memory is useful for ef…