相关论文: ChangeQuery: Advancing Remote Sensing Change Analy…

In recent years, advanced research has focused on the direct learning and analysis of remote sensing images using natural language processing (NLP) techniques. The ability to accurately describe changes occurring in multi-temporal remote…

Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the Earth undergoes global warming. It is difficult to predict when and where an incident will occur, so timely emergency response is critical to…

In recent decades, wildfires, as widespread and extremely destructive natural disasters, have caused tremendous property losses and fatalities, as well as extensive damage to forest ecosystems. Many fire risk assessment projects have been…

The DETR-like segmentors have underpinned the most recent breakthroughs in semantic segmentation, which end-to-end train a set of queries representing the class prototypes or target segments. Recently, masked attention is proposed to…

Explainable AI (XAI) is a promising means of supporting human-AI collaborations for high-stakes visual detection tasks, such as damage detection tasks from satellite imageries, as fully-automated approaches are unlikely to be perfectly safe…

Autonomous driving systems have made significant advances in Q&A, perception, prediction, and planning based on local visual information, yet they struggle to incorporate broader navigational context that human drivers routinely utilize. We…

Cloud contamination severely degrades the usability of remote sensing imagery and poses a fundamental challenge for downstream Earth observation tasks. Recently, diffusion-based models have emerged as a dominant paradigm for remote sensing…

This paper presents a reactive planning system that enriches the topological representation of an environment with a tightly integrated semantic representation, achieved by incorporating and exploiting advances in deep perceptual learning…

This paper aims at designing of adaptive framework for supporting collaborative work of different actors in public safety and disaster recovery missions. In such scenarios, firemen and robots interact to each other to reach a common goal;…

Deep research has emerged as a transformative capability for autonomous agents, empowering Large Language Models to navigate complex, open-ended tasks. However, realizing its full potential is hindered by critical limitations, including…

Monitoring changes triggered by mining activities is crucial for industrial controlling, environmental management and regulatory compliance, yet it poses significant challenges due to the vast and often remote locations of mining sites.…

Bi-temporal change detection at scale based on Very High Resolution (VHR) images is crucial for Earth monitoring. This remains poorly addressed so far: methods either require large volumes of annotated data (semantic case), or are limited…

Graphical User Interface (GUI) Agents, powered by large language and vision-language models, hold promise for enabling end-to-end automation in digital environments. However, their progress is fundamentally constrained by the scarcity of…

The first responder community has traditionally relied on calls from the public, officially-provided geographic information and maps for coordinating actions on the ground. The ubiquity of social media platforms created an opportunity for…

Accurate assessment of post-disaster damage is essential for prioritizing emergency response, yet current practices rely heavily on manual interpretation of satellite imagery.This approach is time-consuming, subjective, and difficult to…

Designers rely on visual search to explore and develop ideas in early design stages. However, designers can struggle to identify suitable text queries to initiate a search or to discover images for similarity-based search that can…

Current visual question answering (VQA) tasks often require constructing multimodal datasets and fine-tuning visual language models, which demands significant time and resources. This has greatly hindered the application of VQA to…

Earthquakes have a significant impact on societies and economies, driving the need for effective search and rescue strategies. With the growing role of AI and robotics in these operations, high-quality synthetic visual data becomes crucial.…

Social media such as tweets are emerging as platforms contributing to situational awareness during disasters. Information shared on Twitter by both affected population (e.g., requesting assistance, warning) and those outside the impact zone…

Remote sensing image change captioning (RSICC) aims at generating human-like language to describe the semantic changes between bi-temporal remote sensing image pairs. It provides valuable insights into environmental dynamics and land…