EMSFomer: Efficient Multi-Scale Transformer for Real-Time Semantic Segmentation
Transformer-based models have achieved impressive performance in semantic segmentation in recent years. However, the multi-head self-attention mechanism in Transformers incurs significant computational overhead and becomes impractical for real-time applications due to its high complexity and large l...
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Main Authors: | Zhengyu Xia, Joohee Kim |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10852306/ |
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