6 papers
Generalizable Knowledge Distillation from Vision Foundation Models for Semantic Segmentation
Chonghua Lv, Dong Zhao, Shuang Wang +4
Knowledge distillation (KD) has been widely applied in semantic segmentation to compress large models, but conventional approaches primarily preserve in-domain accuracy while negle…
Multi-Expert Learning Framework with the State Space Model for Optical and SAR Image Registration
Wei Wang, Dou Quan, Ning Huyan +4
Optical and Synthetic Aperture Radar (SAR) image registration is crucial for multi-modal image fusion and applications. However, several challenges limit the performance of existin…
Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection
Dou Quan, Rufan Zhou, Shuang Wang +4
Deep learning methods have shown promising performances in remote sensing image change detection (CD). However, existing methods usually train a dataset-specific deep network for e…
Generalization-aware Remote Sensing Change Detection via Domain-agnostic Learning
Qi Zang, Shuang Wang, Dong Zhao +3
Change detection has essential significance for the region's development, in which pseudo-changes between bitemporal images induced by imaging environmental factors are key challen…
FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation
Dong Zhao, Jinlong Li, Shuang Wang +4
Vision Foundation Models (VFMs) excel in generalization due to large-scale pretraining, but fine-tuning them for Domain Generalized Semantic Segmentation (DGSS) while maintaining t…
ChangeDiff: A Multi-Temporal Change Detection Data Generator with Flexible Text Prompts via Diffusion Model
Qi Zang, Jiayi Yang, Shuang Wang +3
Data-driven deep learning models have enabled tremendous progress in change detection (CD) with the support of pixel-level annotations. However, collecting diverse data and manuall…