Awesome
SEMA
We constructed a novel indoor dataset VDT-2048-5i for the three-modal images few-shot semantic
segmentation task. We also proposed a Self-Enhanced Mixed Attention Network (SEMANet), which
consists of a Self-Enhanced module (SE) and a Mixed Attention module (MA).
Download the dataset and code
The dataset and code are available at:https://pan.baidu.com/s/1jrhIqOnFbjHcgAcoCPl2jw?pwd=8gya
Paper
https://www.mdpi.com/1424-8220/23/14/6612
Citation
Song, K.; Zhang, Y.; Bao, Y.; Zhao, Y.; Yan, Y. Self-Enhanced Mixed Attention Network for Three-Modal Images Few-Shot Semantic Segmentation. Sensors 2023, 23, 6612.
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[2] BMDENet: Bi-directional Modality Difference Elimination Network for Few-shot RGB-T Semantic Segmentation [J]. IEEE Transactions on Circuits and Systems II Express Briefs, 2023 https://github.com/VDT-2048/BMDENet
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[3] MFFNet: Multi-modal Feature Fusion Network for VDT Salient Object Detection[J]. IEEE Transactions on Multimedia, 2023. https://ieeexplore.ieee.org/abstract/document/10171982
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https://github.com/Lx-Bao/QSFNet
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Related Survey
RGB-T Image Analysis Technology and Application: A Survey [J]. Engineering Applications of Artificial Intelligence, 2023, 120, 105919. https://www.sciencedirect.com/science/article/abs/pii/S0952197623001033