State-of-the-art computer vision systems are trained to predict a fixed set of predetermined
object categories. This restricted form of supervision limits their generality and usability since …

Worldwide Geo-localization aims to pinpoint the precise location of images taken anywhere
on Earth. This task has considerable challenges due to the immense variation in geographic …

Understanding the genetic and molecular drivers of phenotypic heterogeneity across
individuals is central to biology. As new technologies enable fine-grained and spatially …

Contrastive learning methods have significantly narrowed the gap between supervised and
unsupervised learning on computer vision tasks. In this paper, we explore their application …

Lifelong place recognition is an essential and challenging task in computer vision with vast
applications in robust localization and efficient large-scale 3D reconstruction. Progress is …

The problem of localization on a geo-referenced aerial/satellite map given a query ground
view image remains challenging due to the drastic change in viewpoint that causes …

Abstract People increasingly use Social Media (SM) platforms such as Twitter and Facebook
during disasters and emergencies to post situational updates including reports of injured or …

In recent years visual place recognition (VPR), ie, the problem of recognizing the location of
images, has received considerable attention from multiple research communities, spanning …

The task of large-scale retrieval-based image localization is to estimate the geographical
location of a query image by recognizing its nearest reference images from a city-scale …

This paper presents a hardness-aware deep metric learning (HDML) framework. Most
previous deep metric learning methods employ the hard negative mining strategy to …