10 papers · 1 filter
Masks Can Talk: Extracting Structured Text Information from Single-Modal Images for Remote Sensing Change Detection
Kai Zheng, Hang-Cheng Dong, Jiatong Pan +3
Remote sensing change detection is pivotal for urban monitoring, disaster assessment, and environmental resource management. Yet, unimodal deep learning methods frequently confuse…
Tri-path DINO: Feature Complementary Learning for Remote Sensing Multi-Class Change Detection
Kai Zheng, Hang-Cheng Dong, Shoulei Liu +4
In remote sensing imagery, multi class change detection (MCD) is crucial for fine grained monitoring, yet it has long been constrained by complex scene variations and the scarcity…
VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm
Zhenkai Wu, Xiaowen Ma, Zhenliang Ni +4
Vision-language models (VLMs) excel at image understanding tasks, but the large number of visual tokens imposes significant computational costs, hindering deployment on mobile devi…
Changes in Gaza: DINOv3-Powered Multi-Class Change Detection for Damage Assessment in Conflict Zones
Kai Zheng, Zhenkai Wu, Fupeng Wei +6
Accurately and swiftly assessing damage from conflicts is crucial for humanitarian aid and regional stability. In conflict zones, damaged zones often share similar architectural st…
CDXLSTM: Boosting Remote Sensing Change Detection with Extended Long Short-Term Memory
Zhenkai Wu, Xiaowen Ma, Rongrong Lian +2
In complex scenes and varied conditions, effectively integrating spatial-temporal context is crucial for accurately identifying changes. However, current RS-CD methods lack a balan…
Center-guided Classifier for Semantic Segmentation of Remote Sensing Images
Wei Zhang, Mengting Ma, Yizhen Jiang +4
Compared with natural images, remote sensing images (RSIs) have the unique characteristic. i.e., larger intraclass variance, which makes semantic segmentation for remote sensing im…