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

19 citations · 23 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Earth Surface Immune System for Rapid Monitoring of Unknown Anomalies

Jingtao Li, Qian Zhu, Xinyu Wang +3

Earth surface anomalies, driven by escalating climate change, and expanding human activities, are increasing in both frequency and diversity, yet their limited historical data and…

cs.CV2026

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…

cs.CV2024★ 1 cited

Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model

Zhuo Zheng, Stefano Ermon, Dongjun Kim +2

Our understanding of the temporal dynamics of the Earth's surface has been advanced by deep vision models, which often require lots of labeled multi-temporal images for training. H…

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.CV2024★ 3 cited

Segment Any Change

Zhuo Zheng, Yanfei Zhong, Liangpei Zhang +1

Visual foundation models have achieved remarkable results in zero-shot image classification and segmentation, but zero-shot change detection remains an open problem. In this paper,…