34 citations · 79 across the 19 of their papers we have counts for
7 papers · 1 filter
UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision Language Models
Yujie Li, Wenjia Xu, Guangzuo Li +4
The domain gap between remote sensing imagery and natural images has recently received widespread attention and Vision-Language Models (VLMs) have demonstrated excellent generaliza…
Using a negative spatial auto-correlation index to evaluate and improve intrinsic TagMap's multi-scale visualization capabilities
Zhiwei Wei, Nai Yang
The popularity of tag clouds has sparked significant interest in the geographic research community, leading to the development of map-based adaptations known as intrinsic tag maps.…
Optimized 3D Point Labeling with Leaders Using the Beams Displacement Method
Zhiwei Wei, Nai Yang, Wenjia Xu +4
In three-dimensional geographical scenes, adding labels with leader lines to point features can significantly improve their visibility. Leadered labels have a large degree of freed…
Generating grid maps via the snake model
Zhiwei Wei, Nai Yang, Wenjia Xu +1
The grid map, often referred to as the tile map, stands as a vital tool in geospatial visualization, possessing unique attributes that differentiate it from more commonly known tec…
RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
Wenjia Xu, Zijian Yu, Boyang Mu +3
Recent advances in Multimodal Large Language Models (MLLMs) have shown promise for remote sensing tasks such as visual question answering and scene understanding. However, existing…
UAV-VisLoc: A Large-scale Dataset for UAV Visual Localization
Wenjia Xu, Yaxuan Yao, Jiaqi Cao +4
The application of unmanned aerial vehicles (UAV) has been widely extended recently. It is crucial to ensure accurate latitude and longitude coordinates for UAVs, especially when t…
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene Classification
Wenjia Xu, Jiuniu Wang, Zhiwei Wei +2
Deep neural networks have achieved promising progress in remote sensing (RS) image classification, for which the training process requires abundant samples for each class. However,…