SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025, CCF-A, 2024
This work develops omni-scale context modeling for semantic segmentation with state space models and local attention.
Recommended citation: Yunxiang Fu, Meng Lou, Yizhou Yu. "SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation." IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
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