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20182023
most citedOnline Fall Detection using Recurrent Neural Networks

90 citations · 104 across the 21 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.RO2022★ 4 cited

Sampling, Communication, and Prediction Co-Design for Synchronizing the Real-World Device and Digital Model in Metaverse

Zhen Meng, Changyang She, Guodong Zhao +1

The metaverse has the potential to revolutionize the next generation of the Internet by supporting highly interactive services with the help of Mixed Reality (MR) technologies; sti…

cs.CV2022

BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDAR

Georgi Pramatarov, Daniele De Martini, Matthew Gadd +1

This paper is about extremely robust and lightweight localisation using LiDAR point clouds based on instance segmentation and graph matching. We model 3D point clouds as fully-conn…

cs.RO2022

What Goes Around: Leveraging a Constant-curvature Motion Constraint in Radar Odometry

Roberto Aldera, Matthew Gadd, Daniele De Martini +1

This paper presents a method that leverages vehicle motion constraints to refine data associations in a point-based radar odometry system. By using the strong prior on how a non-ho…

cs.CV2022

Depth-SIMS: Semi-Parametric Image and Depth Synthesis

Valentina Musat, Daniele De Martini, Matthew Gadd +1

In this paper we present a compositing image synthesis method that generates RGB canvases with well aligned segmentation maps and sparse depth maps, coupled with an in-painting net…

cs.RO2022★ 1 cited

Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry

Robert Weston, Matthew Gadd, Daniele De Martini +2

Masking By Moving (MByM), provides robust and accurate radar odometry measurements through an exhaustive correlative search across discretised pose candidates. However, this dense…