3 papers
cs.CV2026
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…
eess.IV2026
Dual-Branch State-Displacement Network for Sea Surface Temperature Super-Resolution
Wankun Chen, Feng Gao, Yanhai Gan +4
Sea surface temperature (SST) is a critical indicator of global climate change, yet satellite-derived SST imagery often suffers from coarse spatial resolution, limiting the ability…
cs.CV2026
Frequency and Edge-Guided Segment Anything Model for Remote Sensing Image Semantic Segmentation
Feng Gao, Zizhe Pan, Haoting Wang +4
Remote sensing image semantic segmentation (RSISS) has attracted significant attention due to the growing demand for fine-grained land cover information. The Segment Anything Model…