93 citations · 220 across the 9 of their papers we have counts for
4 papers · 2 filters
See the Future, Classify the Present: Stochastic Latent World Modeling for Hyperspectral Images
Muhammad Ahmad, Gemine Vivone, Ronny Hänsch +3
Hyperspectral image classification (HSIC) relies on static spatial-spectral representations learned from labeled samples, limiting its ability to model structured dependencies in t…
A Geometric-Transformation Feature-Adaptive Manifold Restoration Method for Open-Vocabulary Semantic Segmentation of Remote Sensing Images
Jianzheng Wang, Huan Ni, Xiaonan Niu +2
The semantic information of objects in remote sensing images is typically invariant to geometric transformations from the dihedral group D4. However, SAM3-based open-vocabulary sem…
Bridging the Gap between Labeled and Unlabeled Data via Unified Flow with Feature Memory Bank
Shanwen Wang, Xin Sun, Danfeng Hong +2
Although semi-supervised semantic segmentation () utilizes abundant unlabeled data to reduce manual labeling burdens, independent training of labeled and unlabeled data…
Vision-Language Model Purified Semi-Supervised Semantic Segmentation for Remote Sensing Images
Shanwen Wang, Xin Sun, Danfeng Hong +1
The semi-supervised semantic segmentation (S4) can learn rich visual knowledge from low-cost unlabeled images. However, traditional S4 architectures all face the challenge of low-q…