activity
20232025
most citedSingle-Temporal Supervised Learning for Universal Remote Sensing Change Detection

19 citations · 19 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Towards Comprehensive Interactive Change Understanding in Remote Sensing: A Large-scale Dataset and Dual-granularity Enhanced VLM

Junxiao Xue, Quan Deng, Xuecheng Wu +7

Remote sensing change understanding (RSCU) is essential for analyzing remote sensing images and understanding how human activities affect the environment. However, existing dataset…

cs.CV2025

DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understanding

Weihao Xuan, Junjue Wang, Heli Qi +5

Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in visual understanding, but their application to long-term Earth observation analysis remains li…

cs.CV2025

HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagery

Jingtao Li, Yingyi Liu, Xinyu Wang +9

Advanced interpretation of hyperspectral remote sensing images benefits many precise Earth observation tasks. Recently, visual foundation models have promoted the remote sensing in…

cs.CV2024

Reverse Refinement Network for Narrow Rural Road Detection in High-Resolution Satellite Imagery

Ningjing Wang, Xinyu Wang, Yang Pan +2

The automated extraction of rural roads is pivotal for rural development and transportation planning, serving as a cornerstone for socio-economic progress. Current research primari…

cs.CV2024

AnomalyCD: A benchmark for Earth anomaly change detection with high-resolution and time-series observations

Jingtao Li, Qian Zhu, Xinyu Wang +2

Various Earth anomalies have destroyed the stable, balanced state, resulting in fatalities and serious destruction of property. With the advantages of large-scale and precise obser…

cs.CV2024★ 19 cited

Single-Temporal Supervised Learning for Universal Remote Sensing Change Detection

Zhuo Zheng, Yanfei Zhong, Ailong Ma +1

Bitemporal supervised learning paradigm always dominates remote sensing change detection using numerous labeled bitemporal image pairs, especially for high spatial resolution (HSR)…

cs.CV2023

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…