162 citations · 193 across the 8 of their papers we have counts for
9 papers
EarthVL: A Progressive Earth Vision-Language Understanding and Generation Framework
Junjue Wang, Yanfei Zhong, Zihang Chen +3
Earth vision has achieved milestones in geospatial object recognition but lacks exploration in object-relational reasoning, limiting comprehensive scene understanding. To address t…
EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question Answering
Junjue Wang, Zhuo Zheng, Zihang Chen +2
Earth vision research typically focuses on extracting geospatial object locations and categories but neglects the exploration of relations between objects and comprehensive reasoni…
Seeing Beyond the Patch: Scale-Adaptive Semantic Segmentation of High-resolution Remote Sensing Imagery based on Reinforcement Learning
Yinhe Liu, Sunan Shi, Junjue Wang +1
In remote sensing imagery analysis, patch-based methods have limitations in capturing information beyond the sliding window. This shortcoming poses a significant challenge in proce…
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection from Multi-Source Satellite Imagery
Omid Ghorbanzadeh, Yonghao Xu, Hengwei Zhao +12
The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the Institute of Advanced Research in Artificial Intelligence (IARAI) are presented here. The obj…
AutoLC: Search Lightweight and Top-Performing Architecture for Remote Sensing Image Land-Cover Classification
Chenyu Zheng, Junjue Wang, Ailong Ma +1
Land-cover classification has long been a hot and difficult challenge in remote sensing community. With massive High-resolution Remote Sensing (HRS) images available, manually and…
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
Junjue Wang, Zhuo Zheng, Ailong Ma +2
Deep learning approaches have shown promising results in remote sensing high spatial resolution (HSR) land-cover mapping. However, urban and rural scenes can show completely differ…