10 papers
SegEarth-OV3: Exploring SAM 3 for Open-Vocabulary Semantic Segmentation in Remote Sensing Images
Kaiyu Li, Shengqi Zhang, Yujie Wang +4
Most existing methods for training-free open-vocabulary semantic segmentation are based on CLIP. While these approaches have made progress, they often face challenges in precise lo…
Designing Domain-Specific Agents via Hierarchical Task Abstraction Mechanism
Kaiyu Li, Jiayu Wang, Zhi Wang +4
LLM-driven agents, particularly those using general frameworks like ReAct or human-inspired role-playing, often struggle in specialized domains that necessitate rigorously structur…
Interpretable Machine Learning for Urban Heat Mitigation: Attribution and Weighting of Multi-Scale Drivers
David Tschan, Zhi Wang, Dominik Strebel +2
Urban heat islands (UHIs) are often accentuated during heat waves (HWs) and pose a public health risk. Mitigating UHIs requires urban planners to first estimate how urban heat is i…
DescribeEarth: Describe Anything for Remote Sensing Images
Kaiyu Li, Zixuan Jiang, Xiangyong Cao +4
Automated textual description of remote sensing images is crucial for unlocking their full potential in diverse applications, from environmental monitoring to urban planning and di…
Annotation-Free Open-Vocabulary Segmentation for Remote-Sensing Images
Kaiyu Li, Xiangyong Cao, Ruixun Liu +4
Semantic segmentation of remote sensing (RS) images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high exp…
SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model
Kaiyu Li, Zepeng Xin, Li Pang +7
Remote sensing has become critical for understanding environmental dynamics, urban planning, and disaster management. However, traditional remote sensing workflows often rely on ex…