Search Results for author:
Found 8 papers, 4 papers with code
Boosting Performance of a Baseline Visual Place Recognition Technique by Predicting the Maximally Complementary Technique
One recent promising approach to the Visual Place Recognition (VPR) problem has been to fuse the place recognition estimates of multiple complementary VPR techniques using methods such as SRAL and multi-process fusion.
Improving Worst Case Visual Localization Coverage via Place-specific Sub-selection in Multi-camera Systems
6-DoF visual localization systems utilize principled approaches rooted in 3D geometry to perform accurate camera pose estimation of images to a map.
Unsupervised Complementary-aware Multi-process Fusion for Visual Place Recognition
A recent approach to the Visual Place Recognition (VPR) problem has been to fuse the place recognition estimates of multiple complementary VPR techniques simultaneously.
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
Visual Place Recognition is a challenging task for robotics and autonomous systems, which must deal with the twin problems of appearance and viewpoint change in an always changing world.
Ranked #1 on
Visual Localization
on RobotCar Seasons v2
Hierarchical Multi-Process Fusion for Visual Place Recognition
In this paper we present a novel, hierarchical localization system that explicitly benefits from three varying characteristics of localization techniques: the distribution of their localization hypotheses, their appearance- and viewpoint-invariant properties, and the resulting differences in where in an environment each system works well and fails.
Filter Early, Match Late: Improving Network-Based Visual Place Recognition
Our key innovation is to filter the feature maps in an early convolutional layer, but then continue to run the network and extract a feature vector using a later layer in the same network.
Multi-Process Fusion: Visual Place Recognition Using Multiple Image Processing Methods
In this paper we address these shortcomings with a novel "multi-sensor" fusion approach applied to multiple image processing methods for a single visual image stream, combined with a dynamic sequence matching length technique and an automatic processing method weighting scheme.
Robotics
Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation
Visual place recognition (VPR) - the act of recognizing a familiar visual place - becomes difficult when there is extreme environmental appearance change or viewpoint change.
Robotics
