In recent years, the remote sensing image (RSI) semantic segmentation attracts increasing
research interest due to its wide application. RSIs are difficult to be processed holistically on …

As unconventional sources of geoinformation, massive imagery and text messages from
open platforms and social media form a temporally quasi-seamless, spatially …

In the rapidly evolving field of remote sensing, Deep Learning (DL) techniques have become
pivotal in interpreting and processing complex datasets. However, the increasing reliance …

This paper aims to develop an accurate 3D geometry representation of satellite images
using satellite-ground image pairs. Our focus is on the challenging problem of 3D-aware …

This paper aims at achieving fine-grained building attribute segmentation in a cross-view
scenario ie using satellite and street-view image pairs. The main challenge lies in …

Though semantic segmentation has been heavily explored in vision literature, unique
challenges remain in the remote sensing domain. One such challenge is how to handle …

The task of multimedia geolocation is becoming an increasingly essential component of the
digital forensics toolkit to effectively combat human trafficking, child sexual exploitation, and …

With advanced neural network techniques, language models can generate content that
looks genuinely created by humans. Such advanced progress benefits society in numerous …

Images captured in dusty environments suffering from poor visibility and quality.
Enhancement of these images such as sand dust images plays a critical role in various …

This work addresses the task of modeling spatiotemporal traffic patterns directly from
overhead imagery, which we refer to as image-driven traffic modeling. We extend this line of …