activity
20172025
most citedGCNv2: Efficient Correspondence Prediction for Real-Time SLAM

23 citations · 40 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2025

Information Gain Is Not All You Need

Ludvig Ericson, José Pedro, Patric Jensfelt

Autonomous exploration in mobile robotics often involves a trade-off between two objectives: maximizing environmental coverage and minimizing the total path length. In the widely u…

cs.CV2024

ExelMap: Explainable Element-based HD-Map Change Detection and Update

Lena Wild, Ludvig Ericson, Rafael Valencia +1

Acquisition and maintenance are central problems in deploying high-definition (HD) maps for autonomous driving, with two lines of research prevalent in current literature: Online H…

cs.RO2024★ 9 cited

Beyond the Frontier: Predicting Unseen Walls from Occupancy Grids by Learning from Floor Plans

Ludvig Ericson, Patric Jensfelt

In this paper, we tackle the challenge of predicting the unseen walls of a partially observed environment as a set of 2D line segments, conditioned on occupancy grids integrated al…

cs.RO2022

FloorGenT: Generative Vector Graphic Model of Floor Plans for Robotics

Ludvig Ericson, Patric Jensfelt

Floor plans are the basis of reasoning in and communicating about indoor environments. In this paper, we show that by modelling floor plans as sequences of line segments seen from…

cs.RO2019★ 23 cited

GCNv2: Efficient Correspondence Prediction for Real-Time SLAM

Jiexiong Tang, Ludvig Ericson, John Folkesson +1

In this paper, we present a deep learning-based network, GCNv2, for generation of keypoints and descriptors. GCNv2 is built on our previous method, GCN, a network trained for 3D pr…

cs.AI2017★ 8 cited

On the Performance of Network Parallel Training in Artificial Neural Networks

Ludvig Ericson, Rendani Mbuvha

Artificial Neural Networks (ANNs) have received increasing attention in recent years with applications that span a wide range of disciplines including vital domains such as medicin…