25 citations · 53 across the 8 of their papers we have counts for
8 papers
Exchange Is All You Need for Remote Sensing Change Detection
Sijun Dong, Siming Fu, Kaiyu Li +3
Remote sensing change detection fundamentally relies on the effective fusion and discrimination of bi-temporal features. Prevailing paradigms typically utilize Siamese encoders bri…
Disentangling Content from Style to Overcome Shortcut Learning: A Hybrid Generative-Discriminative Learning Framework
Siming Fu, Sijun Dong, Xiaoliang Meng
Despite the remarkable success of Self-Supervised Learning (SSL), its generalization is fundamentally hindered by Shortcut Learning, where models exploit superficial features like…
PeftCD: Leveraging Vision Foundation Models with Parameter-Efficient Fine-Tuning for Remote Sensing Change Detection
Sijun Dong, Yuxuan Hu, LiBo Wang +2
To tackle the prevalence of pseudo changes, the scarcity of labeled samples, and the difficulty of cross-domain generalization in multi-temporal and multi-source remote sensing ima…
CFNet: Optimizing Remote Sensing Change Detection through Content-Aware Enhancement
Fan Wu, Sijun Dong, Xiaoliang Meng
Change detection is a crucial and widely applied task in remote sensing, aimed at identifying and analyzing changes occurring in the same geographical area over time. Due to variab…
A Remote Sensing Image Change Detection Method Integrating Layer Exchange and Channel-Spatial Differences
Sijun Dong, Fangcheng Zuo, Geng Chen +2
Change detection in remote sensing imagery is a critical technique for Earth observation, primarily focusing on pixel-level segmentation of change regions between bi-temporal image…
EfficientCD: A New Strategy For Change Detection Based With Bi-temporal Layers Exchanged
Sijun Dong, Yuwei Zhu, Geng Chen +1
With the widespread application of remote sensing technology in environmental monitoring, the demand for efficient and accurate remote sensing image change detection (CD) for natur…
PyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing Imagery
Libo Wang, Dongxu Li, Sijun Dong +3
Semantic segmentation, as a basic tool for intelligent interpretation of remote sensing images, plays a vital role in many Earth Observation (EO) applications. Nowadays, accurate s…
MetaSegNet: Metadata-collaborative Vision-Language Representation Learning for Semantic Segmentation of Remote Sensing Images
Libo Wang, Sijun Dong, Ying Chen +3
Semantic segmentation of remote sensing images plays a vital role in a wide range of Earth Observation applications, such as land use land cover mapping, environment monitoring, an…