24 citations · 25 across the 7 of their papers we have counts for
7 papers
Real-World Knowledge-Guided Change Data Synthesis for Remote Sensing
Yaoyi Qi, Xingxing Weng, Chao Pang +5
Change data synthesis provides a cost-effective solution for expanding training data and improving the performance of change detection models. However, existing synthesis methods t…
LongEarth-R1: Benchmarking and Aligning Vision-Language Models for Long-Horizon Earth Observation Reasoning
Yupan Ding, Jing Xiao, Zhenyuan Zhang +4
Long-horizon Earth observation reasoning requires models to organize multi-stage geographic evolution, localize spatial changes, detect temporal anomalies, and infer future from ex…
Observe Less, Understand More: Cost-aware Cross-scale Observation for Remote Sensing Understanding
Zhenghao Xie, Jing Xiao, Zhenqi Wang +4
Remote sensing understanding inherently requires multi-resolution observation, since different targets and application tasks demand different levels of spatial detail. While low-re…
Continual Vision-Language Learning for Remote Sensing: Benchmarking and Analysis
Xingxing Weng, Ruifeng Ni, Chao Pang +5
Current remote sensing vision-language models (RS VLMs) demonstrate impressive performance in image interpretation but rely on static training data, limiting their ability to accom…
DragOSM: Extract Building Roofs and Footprints from Aerial Images by Aligning Historical Labels
Kai Li, Xingxing Weng, Yupeng Deng +4
Extracting polygonal roofs and footprints from remote sensing images is critical for large-scale urban analysis. Most existing methods rely on segmentation-based models that assume…
Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives
Xingxing Weng, Chao Pang, Gui-Song Xia
Vision-language modeling (VLM) aims to bridge the information gap between images and natural language. Under the new paradigm of first pre-training on massive image-text pairs and…
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…